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Autor: Grafiati
Data publikacji: 4 czerwca 2021
Data aktualizacji: 8 czerwca 2024

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1

Mabrouk, Emad Hamdy Ahmed. "Meta-Heuristics Programming and Its Applications". 京都大学 (Kyoto University), 2011. http://hdl.handle.net/2433/142132.

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2

Koshich, P. A. "University course timetabling of meta-heuristics". Thesis, University of Oxford, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.433470.

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3

Vázquez, Rodríguez José Antonio. "Meta-hyper-heuristics for hybrid flow shops". Thesis, University of Essex, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.438147.

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4

Gabaldon, Ponsa Eloi. "Meta-Heuristics for Scheduling in Cluster Federated Environments". Doctoral thesis, Universitat de Lleida, 2018. http://hdl.handle.net/10803/462072.

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Avui en dia, moltes organitzacions, empreses o universitats han anat acumulant, durant anys, un gran nombre de recursos computacionals agrupats en clústers. Els Entorns Clúster Federats sorgeixen com una nova arquitectura amb l’objectiu d’unir tots aquests recursos, augmentant la capacitat de còmput global de l’organització sense haver de fer una gran inversió econòmica. No obstant això, l’elevat nombre de màquines i recursos computacionals, comporten un gran consum energètic. A causa de les connotacions econòmiques i sostenibles que això implica, recentment s’ha obert una nova línia d’investigació que s’ha centrat a reduir el consum d’energia i maximitzar el rendiment de les aplicacions i la utilització dels recursos computacionals . La planificació en aquests entorns, responsable d’assignar les aplicacions als recursos del sistema, ofereix la possibilitat d’obtenir grans millores, ja que gestionar correctament els recursos pot tenir un gran impacte en el rendiment del sistema i en l’eficiència energètica. Tanmateix, aquest procés és molt complex, ja que pertany al grup de problemes NP. Aquesta tesi estudia el problema de la planificació de grans workloads extrets de diverses traces reals. Les tècniques proposades consideren l’heterogeneïtat dels recursos del sistema, així com també la capacitat d’aplicar la co-assignació per aprofitar els recursos sobrants de cada clúster. Les propostes utilitzaran tàctiques sofisticades multi-criteri, basades en Algoritmes Genètics i Particle Swarm Optimization centrades en la reducció tant del temps d’execució dels treballs com del consum energètic del sistema. Els resultats mostren l’efectivitat dels mètodes proposats, proporcionant solucions que milloren el rendiment respecte a altres tècniques presents en la literatura. Obrint una nova i interessant línia d’investigació en el camp de la planificació en entorns altament distribuïts i heterogenis.
Hoy en día, muchas organizaciones, empresas o universidades han ido acumulando, durante años, un gran número de recursos agrupados en clústeres. Los Entornos Cluster Federados surgen como una nueva arquitectura con el objetivo de unir todos estos recursos, aumentando la capacidad de cómputo global de la organización sin tener que hacer una gran inversión económica. Sin embargo, el elevado número de máquinas y recursos de computo, comportan un gran consumo energético. Debido a las connotaciones económicas y sostenibles que ello implica, recientemente se ha abierto una nueva línea de investigación que se ha centrado en reducir el consumo de energía y maximizar el rendimiento de las aplicaciones y utilización de los recursos. La planificación en estos entornos, responsable de asignar las aplicaciones a los recursos del sistema, ofrece la posibilidad de obtener grandes mejoras, ya que gestionar correctamente los recursos puede tener un gran impacto en el rendimiento del sistema y en la eficiencia energética. Sin embargo, este proceso es muy complejo, ya que pertenece al grupo de problemas NP. Esta tesis estudia el problema de la planificación de grandes workloads extraídos de distintas trazas reales. Las técnicas propuestas consideran la heterogeneidad de los recursos del sistema, así como también la capacidad de aplicar la co-asignación para aprovechar los recursos sobrantes de cada clúster. Las propuestas utilizarán tácticas sofisticadas multi-criterio, basadas en Algoritmos Genéticos y Particle Swarm Optimization centradas en la reducción tanto del tiempo de ejecución de los trabajos como del consumo energético del sistema. Los resultados muestran la efectividad de los métodos propuestos, proporcionando soluciones que mejoran el rendimiento respecto a otras técnicas presentes en la literatura. Abriendo una nueva e interesante línea de investigación en el campo de la planificación en entornos altamente distribuidos y heterogéneos.
Many organizations, companies or universities have accumulated, over the years, a large number of computing resources grouped in Clusters. Cluster Federated Environments arise as a new architecture with the objective of joining all these resources, increasing the global computing capacity of the organization without making a great economic investment. However, the high number of machines and computing resources imples great energy consumption. Due to the economic and sustainable connotations that this entails, recently a new line of investigation has focused on reducing energy consumption while maximizing the performance of the applications and the usage of the system. The scheduling in these environments, responsible for allocating the applications to the system resources, offers the possibility of obtaining great improvements, as managing the resources correctly can have a great impact on the system performance and energy efficiency. However, this process is very complex, since it belongs to the NP problem group. This PhD studies the problem of scheduling large batch workloads extracted from diverse real traces. The proposed techniques consider the heterogeneity of the system resources as well as the ability to apply co-allocation in order to take advantage of the leftover resources across clusters. The proposals will use sophisticated multi-criteria tactics, based on Genetic Algorithms and Particle Swarm Optimization, focused on reducing both the execution time of the jobs and the energy consumption of the system. The results show the effectiveness of the proposed methods, which provide solutions that improved the performance compared with other well-known techniques in the literature, opening new and interesting research lines in the scheduling field in highly distributed and heterogeneous environments.
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5

Wang, R. "Berth scheduling at seaports : meta-heuristics and simulation". Thesis, Liverpool John Moores University, 2018. http://researchonline.ljmu.ac.uk/9652/.

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This research aims to develop realistic solutions to enhance the efficiency of port operations. By conducting a comprehensive literature review on logistic problems at seaports, some important gaps have been identified for the first time. The following contributions are made in order to close some of the existing gaps. Firstly, this thesis identifies important realistic features which have not been well-studied in current academic research of berth planning. This thesis then aims to solve a discrete dynamic Berth allocation problem (BAP) while taking tidal constraints into account. As an important feature when dealing with realistic scheduling, changing tides have not been well-considered in BAPs. To the best of our knowledge, there is no existing work using meta-heuristics to tackle the BAP with multiple tides that can provide feasible solutions for all the test cases. We propose one single-point meta-heuristic and one population-based meta-heuristic. With our algorithms, we meet the following goals: (i) to minimise the cost of all vessels while staying in the port, and (ii) to schedule available berths for the arriving vessels taking into account a multi-tidal planning horizon. Comprehensive experiments are conducted in order to analyse the strengths and weaknesses of the algorithms and compare with both exact and approximate methods. Furthermore, lacking tools for examining existing algorithms for different optimisation problems and simulating real-world scenarios is identified as another gap in this study. This thesis develops a discrete-event simulation framework. The framework is able to generate test cases for different problems and provide visualisations. With this framework, contributions include assessing the performance of different algorithms for optimisation problems and benchmarking optimisation problems.
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6

Lü, Haili, i 吕海利. "A comparative study of assembly job shop scheduling using simulation, heuristics and meta-heuristics". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B47029018.

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7

Luis, Martino. "Meta-Heuristics for the Capacitated Multi-Source Weber Problem". Thesis, University of Kent, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.499796.

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8

Mahakala, Kavya Reddy. "Identifying Security Requirements using Meta-Data and Dependency Heuristics". University of Cincinnati / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1543995518151544.

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9

Corry, Paul. "Improving efficiency in an iron foundry using meta-heuristics". Thesis, Queensland University of Technology, 2002.

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10

Ulker, Ozgur. "Office space allocation by using mathematical programming and meta-heuristics". Thesis, University of Nottingham, 2013. http://eprints.nottingham.ac.uk/13604/.

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Office Space Allocation (OSA) is the task of efficient usage of spatial resources of an organisation. A common goal in a typical OSA problem is to minimise the wastage of space either by limiting the overuse or underuse of the facilities. The problem also contains a myriad of hard and soft constraints based on the preferences of respective organisations. In this thesis, the OSA variant usually encountered in academic institutions is investigated. Previous research in this area is rather sparse. This thesis provides a definition, extension, and literature review for the problem as well as a new parametrised data instance generator. In this thesis, two main algorithmic approaches for tackling the OSA are proposed: The first one is integer linear programming. Based on the definition of several constraints and some additional variables, two different mathematical models are proposed. These two models are not strictly alternatives to each other. While one of them provides more performance for the types of instances it is applicable, it lacks generality. The other approach provides less performance; however, it is easier to apply this model to different OSA problems. The second algorithmic approach is based on metaheuristics. A three step process in heuristic development is followed. In the first step, general local search techniques (descent methods, threshold acceptance, simulated annealing, great deluge) traverse within the neighbourhood via random relocation and swap moves. The second step of heuristic development aims to investigate large sections of the whole neighbourhood greedily via very fast cost calculation, cost update, and search for best move procedures within an evolutionary local search framework. The final step involves refinements and hybridisation of best performing (in terms of solution quality) mathematical programming and meta-heuristic techniques developed in prior steps. This thesis aims to be one of the pioneering works in the research area of OSA. The major contributions are: the analysis of the problem, a new parametrised data instance generator, mathematical programming models, and meta-heuristic approaches in order to extend the state-of-the art in this area.
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11

Parkinson, Edward. "Using improvement location and improvement preference to create meta-heuristics". Thesis, City University London, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.407555.

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12

Ries, Jana. "Instance-based flexible parameter tuning for meta-heuristics using fuzzy-logic". Thesis, University of Portsmouth, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.515539.

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13

Wassan, Naveed Ahmed. "Meta-heuristics for the multiple trip vehicle routing problem with backhauls". Thesis, University of Kent, 2016. https://kar.kent.ac.uk/56731/.

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With the growing and more accessible computational power, the demand for robust and sophisticated computerised optimisation is increasing for logistical problems. By making good use of computational technologies, the research in this thesis concentrates on efficient fleet management by studying a class of vehicle routing problems and developing efficient solution algorithms. The literature review in this thesis looks at VRPs from various development angles. The search reveals that from the problem modelling side clear efforts are made to bring the classical VRP models closer to reality by developing various variants. However, apart from the real VRP applications (termed as 'rich' VRPs), it is also noticeable that these classical VRP based variants address merely one or two additional characteristics from the real routing problem issues, concentrating on either operational (fleet management) or tactical (fleet acquisition) aspects. This thesis certainly hopes to add to one of those good efforts which have helped in bringing the VRPs closer to reality through addressing both the operational as well as the tactical aspects. On the solution methodologies development side, the proposed research noted some considerable and impressive developments. Although, it is well established that the VRPs belong to the NP-hard combinatorial class of problems, there are considerable efforts on the development of exact methods. However the literature is full of a variety of heuristic methodologies including the classical and the most modern hybrid approaches. Among the hybrid approaches, the most recent one noted is mat-heuristics that combine heuristics and mathematical programming techniques to solve combinatorial optimisation problems. The mat-heuristics approaches appear to be comparatively in its infant age at this point in time. However this is an exciting area of research which seeks more attention in the literature. Hence, a good part of this research is devoted to the development of a hybrid approach that combines heuristics and mathematical programming techniques. When reviewing the specific literature on the VRP problems focused in this thesis, the vehicle routing problem with backhauls (VRPB) and the multiple trip vehicle routing problem (MT-VRP), there is not sufficient development on the problem modelling side in terms of bringing these two problems closer to the reality. Hence, to fill the gap this thesis introduces and investigates a new variant, the multiple trip vehicle routing problem with backhauls (MT-VRPB) that combines the above two variants of the VRP. The problem is first described thoroughly and a new ILP (Integer Linear Programming) mathematical formulation of the MT-VRPB along with its possible variations is presented. The MT-VRPB is then solved optimally by using CPLEX along with providing an illustrative example showing the validation of the mathematical formulation. As part of the contribution, a large set of MT-VRPB data instances is created which is made available for future benchmarking. The CPLEX implementation produced optimal solutions for a good number of small and medium size data instances of the MT-VRPB and generated lower bounds for all instances. The CPLEX success may be considered as modest, but the produced results proved very important for the validation of the heuristic results produced in the thesis. To solve the larger instances of the MT-VRPB, a two level VNS algorithm called 'Two-Level VNS' is developed. It was noticed from the literature that the choice of using VNS for the VRPs has increased in recent literature due to its simplicity and speed. However our initial experiments with the classical VNS indicated that the algorithm is more inclined towards the intensification side. Hence, the Two-Level VNS is designed to obtain a maximum balance of the diversification and the intensification during the search process. It is achieved by incorporating a sub-set of neighbourhood structures and a sus-set of local search refinement routines and hence, a full set of neighbourhood structures and a full set of local search refinement routines at two levels of the algorithm respectively. The algorithm found very encouraging results when compared with the solutions found by CPLEX. These findings in this thesis demonstrate the power of VNS yet again in terms of its speed, simplicity and efficiency. To investigate this new variant further, we developed an algorithm belonging to the new class of the hybrid methodologies, i.e., mat-heuristics. A hybrid collaborative sequential mat-heuristic approach called the CSMH to solve the MT-VRPB is developed. The exact method approach produced in Chapter 4 is then hybridised with the Two-Level VNS algorithm developed in Chapter 5. The overall performance of the CSMH remained very encouraging in terms of the solution quality and the time taken on average compared with the CPLEX and the Two-Level VNS meta-heuristic. To demonstrate the power and effectiveness of our methodologies, we tested the designed algorithms on the two special versions of the VRP (i.e., VRPB and MT-VRP) to assess whether they are efficient and dynamic enough to solve a range of VRP variants. Hence the Two-Level VNS and the CSMH algorithms developed to solve the MT-VRPB are adapted accordingly and implemented to solve the two above variants separately. The algorithms produced very competitive results for the benchmark data sets when compared to the best known solutions from the literature. The successful implementations of these algorithms on the three VRP models with only minor amendments prove their generalizability and their robustness. The results in this research show that significant cost savings could be obtained by choosing the right fleet size and better vehicle utilisations with multiple trips and backhauling. Hence, the research proved the justification of studying this interesting combination. Moreover, the problem modelling, efficient algorithm design and implementation, and the research results reveal some vital information and implications from the managerial point of view in terms of making the tactical (fleet acquisition) and the operational (fleet management) decisions in a more informative manner.
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14

Türk, Stefan [Verfasser]. "Technology Migration Optimization Of Optical Backbone Networks Using Meta-Heuristics / Stefan Türk". München : Verlag Dr. Hut, 2014. http://d-nb.info/1060587661/34.

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15

Randall, Marcus Christian, i n/a. "A General Modelling System and Meta-Heuristic Based Solver for Combinatorial Optimisation Problems". Griffith University. School of Environmental and Applied Science, 1999. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20051116.120133.

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There are many real world assignment, scheduling and planning tasks which can be classified as combinatorial optimisation problems (COPs). These are usually formulated as a mathematical problem of minimising or maximising some cost function subject to a number of constraints. Usually, such problems are NP hard, and thus, whilst it is possible to find exact solutions to specific problems, in general only approximate solutions can be found. There are many algorithms that have been proposed for finding approximate solutions to COPs, ranging from special purpose heuristics to general search meta-heuristics such as simulated annealing and tabu search. General meta-heuristic algorithms like simulated annealing have been applied to a wide range of problems. In most cases, the designer must choose an appropriate data structure and a set of local operators that define a search neighbourhood. The variability in representation techniques, and suitable neighbourhood transition operators, has meant that it is usually necessary to develop new code for each problem. Toolkits like the one developed by Ingber's Adaptive Simulated Annealing (Ingber 1993, 1996) have been applied to assist rapid prototyping of simulated annealing codes, however, these still require the development of new programs for each type of problem. There have been very few attempts to develop a general meta-heuristic solver, with the notable exception being Connolly's General Purpose Simulated Annealing (Connolly 1992). In this research, a general meta-heuristic based system is presented that is suitable for a wide range of COPs. The main goal of this work is to build an environment in which it is possible to specify a range of COPs using an algebraic formulation, and to produce a tailored solver automatically. This removes the need for the development of specific software, allowing very rapid prototyping. Similar techniques have been available for linear programming based solvers for some years in the form of the GAMS (General Algebraic Modelling System) (Brooke, Kendrick, Meeraus and Raman 1997) and AMPL (Fourer, Gay and Kernighan 1993) interfaces. The new system is based on a novel linked list data structure rather than the more conventional vector notation due to the natural mapping between COPS and lists. In addition, the modelling system is found to be very suitable for processing by meta-heuristic search algorithms as it allows the direct application of common local search operators. A general solver is built that is based on the linked list modelling system. This system is capable of using meta-heuristic search engines such as greedy search, tabu search and simulated annealing. A number of implementation issues such as generating initial solutions, choosing and invoking appropriate local search transition operators and producing suitable incremental cost expressions, are considered. As such, the system can been seen as a good test-bench for model prototypers and those who wish to test various meta-heuristic implementations in a standard way. However, it is not meant as a replacement or substitute for efficient special purpose search algorithms. The solver shows good performance on a wide range of problems, frequently reaching the optimal and best-known solutions. Where this is not the case, solutions within a few percent deviation are produced. Performance is dependent on the chosen transition operators and the frequency with which each is applied. To a lesser extent, the performance of this implementation is influenced by runtime parameters of the meta-heuristic search engine.
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16

Randall, Marcus. "A General Modelling System and Meta-Heuristic Based Solver for Combinatorial Optimisation Problems". Thesis, Griffith University, 1999. http://hdl.handle.net/10072/367399.

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There are many real world assignment, scheduling and planning tasks which can be classified as combinatorial optimisation problems (COPs). These are usually formulated as a mathematical problem of minimising or maximising some cost function subject to a number of constraints. Usually, such problems are NP hard, and thus, whilst it is possible to find exact solutions to specific problems, in general only approximate solutions can be found. There are many algorithms that have been proposed for finding approximate solutions to COPs, ranging from special purpose heuristics to general search meta-heuristics such as simulated annealing and tabu search. General meta-heuristic algorithms like simulated annealing have been applied to a wide range of problems. In most cases, the designer must choose an appropriate data structure and a set of local operators that define a search neighbourhood. The variability in representation techniques, and suitable neighbourhood transition operators, has meant that it is usually necessary to develop new code for each problem. Toolkits like the one developed by Ingber's Adaptive Simulated Annealing (Ingber 1993, 1996) have been applied to assist rapid prototyping of simulated annealing codes, however, these still require the development of new programs for each type of problem. There have been very few attempts to develop a general meta-heuristic solver, with the notable exception being Connolly's General Purpose Simulated Annealing (Connolly 1992). In this research, a general meta-heuristic based system is presented that is suitable for a wide range of COPs. The main goal of this work is to build an environment in which it is possible to specify a range of COPs using an algebraic formulation, and to produce a tailored solver automatically. This removes the need for the development of specific software, allowing very rapid prototyping. Similar techniques have been available for linear programming based solvers for some years in the form of the GAMS (General Algebraic Modelling System) (Brooke, Kendrick, Meeraus and Raman 1997) and AMPL (Fourer, Gay and Kernighan 1993) interfaces. The new system is based on a novel linked list data structure rather than the more conventional vector notation due to the natural mapping between COPS and lists. In addition, the modelling system is found to be very suitable for processing by meta-heuristic search algorithms as it allows the direct application of common local search operators. A general solver is built that is based on the linked list modelling system. This system is capable of using meta-heuristic search engines such as greedy search, tabu search and simulated annealing. A number of implementation issues such as generating initial solutions, choosing and invoking appropriate local search transition operators and producing suitable incremental cost expressions, are considered. As such, the system can been seen as a good test-bench for model prototypers and those who wish to test various meta-heuristic implementations in a standard way. However, it is not meant as a replacement or substitute for efficient special purpose search algorithms. The solver shows good performance on a wide range of problems, frequently reaching the optimal and best-known solutions. Where this is not the case, solutions within a few percent deviation are produced. Performance is dependent on the chosen transition operators and the frequency with which each is applied. To a lesser extent, the performance of this implementation is influenced by runtime parameters of the meta-heuristic search engine.
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Environmental and Applied Science
Science, Environment, Engineering and Technology
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17

Farham, Mohammad Saleh. "Generalization Of Restricted Planar Location Problems: Unified Meta-heuristics For Single Facility Case". Master's thesis, METU, 2013. http://etd.lib.metu.edu.tr/upload/12615417/index.pdf.

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18

Marija, Milojević Jevrić. "The application of meta-heuristics to optimise load distribution in machine elements and assemblies". Phd thesis, Univerzitet u Novom Sadu, Fakultet tehničkih nauka u Novom Sadu, 2015. http://www.cris.uns.ac.rs/record.jsf?recordId=95374&source=NDLTD&language=en.

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In this Phd thesis, heuristic, meta-heuristic and predictive methods areconsidered. Meta-heuristics optimisation of the transverse load distributionfactor of helical and spur gears is conducted. The multi-objective optimisationproblem of the planetary gear train is done using Genetic Algorithm method.A comparative study of several meta-heuristic methods is given for solvingthe problem of dynamic load capacity and working life at radial ball bearings.Bayesian network, as a predictive method, is implemented in the software tosupport the decision making in complex mechanical plants.
Докторска дисертација се бави темама везаним за хеуристичке,метахеуристичке и предикционе методе. Извршена је метахеуристичкаоптимизација проблема трансверзалног фактора расподелеоптерећења код цилиндричног зупчастог пара. Вишекритеријумскипроблем геометрије планетарног преносника је решаван применомгенетских алгоритама. Поређење неколико метахеуристичких метода једато на решавању оптимизационог проблема радног века и динамичкеносивости код котрљајних кугличних лежаја. Бајесове мреже, каопредикциона метода, су уграђене у софтвер за подршку одлучивању укомплексним машинским постројењима.
Doktorska disertacija se bavi temama vezanim za heurističke,metaheurističke i predikcione metode. Izvršena je metaheurističkaoptimizacija problema transverzalnog faktora raspodeleopterećenja kod cilindričnog zupčastog para. Višekriterijumskiproblem geometrije planetarnog prenosnika je rešavan primenomgenetskih algoritama. Poređenje nekoliko metaheurističkih metoda jedato na rešavanju optimizacionog problema radnog veka i dinamičkenosivosti kod kotrljajnih kugličnih ležaja. Bajesove mreže, kaopredikciona metoda, su ugrađene u softver za podršku odlučivanju ukompleksnim mašinskim postrojenjima.
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19

Veluscek, Marco. "Global supply chain optimization : a machine learning perspective to improve caterpillar's logistics operations". Thesis, Brunel University, 2016. http://bura.brunel.ac.uk/handle/2438/13050.

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Supply chain optimization is one of the key components for the effective management of a company with a complex manufacturing process and distribution network. Companies with a global presence in particular are motivated to optimize their distribution plans in order to keep their operating costs low and competitive. Changing condition in the global market and volatile energy prices increase the need for an automatic decision and optimization tool. In recent years, many techniques and applications have been proposed to address the problem of supply chain optimization. However, such techniques are often too problemspecific or too knowledge-intensive to be implemented as in-expensive, and easy-to-use computer system. The effort required to implement an optimization system for a new instance of the problem appears to be quite significant. The development process necessitates the involvement of expert personnel and the level of automation is low. The aim of this project is to develop a set of strategies capable of increasing the level of automation when developing a new optimization system. An increased level of automation is achieved by focusing on three areas: multi-objective optimization, optimization algorithm usability, and optimization model design. A literature review highlighted the great level of interest for the problem of multiobjective optimization in the research community. However, the review emphasized a lack of standardization in the area and insufficient understanding of the relationship between multi-objective strategies and problems. Experts in the area of optimization and artificial intelligence are interested in improving the usability of the most recent optimization algorithms. They stated the concern that the large number of variants and parameters, which characterizes such algorithms, affect their potential applicability in real-world environments. Such characteristics are seen as the root cause for the low success of the most recent optimization algorithms in industrial applications. Crucial task for the development of an optimization system is the design of the optimization model. Such task is one of the most complex in the development process, however, it is still performed mostly manually. The importance and the complexity of the task strongly suggest the development of tools to aid the design of optimization models. In order to address such challenges, first the problem of multi-objective optimization is considered and the most widely adopted techniques to solve it are identified. Such techniques are analyzed and described in details to increase the level of standardization in the area. Empirical evidences are highlighted to suggest what type of relationship exists between strategies and problem instances. Regarding the optimization algorithm, a classification method is proposed to improve its usability and computational requirement by automatically tuning one of its key parameters, the termination condition. The algorithm understands the problem complexity and automatically assigns the best termination condition to minimize runtime. The runtime of the optimization system has been reduced by more than 60%. Arguably, the usability of the algorithm has been improved as well, as one of the key configuration tasks can now be completed automatically. Finally, a system is presented to aid the definition of the optimization model through regression analysis. The purpose of the method is to gather as much knowledge about the problem as possible so that the task of the optimization model definition requires a lower user involvement. The application of the proposed algorithm is estimated that could have saved almost 1000 man-weeks to complete the project. The developed strategies have been applied to the problem of Caterpillar’s global supply chain optimization. This thesis describes also the process of developing an optimization system for Caterpillar and highlights the challenges and research opportunities identified while undertaking this work. This thesis describes the optimization model designed for Caterpillar’s supply chain and the implementation details of the Ant Colony System, the algorithm selected to optimize the supply chain. The system is now used to design the distribution plans of more than 7,000 products. The system improved Caterpillar’s marginal profit on such products by a factor of 4.6% on average.
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Du, Plessis Johan de Villiers. "Investigation into the use of meta-heuristics in the optimisation of log positioning during sawmill processing". Stellenbosch : University of Stellenbosch, 2010. http://hdl.handle.net/10019.1/5209.

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Thesis (MSc (Forest and Wood Science))--University of Stellenbosch, 2011.
ENGLISH ABSTRACT: The percentage yield of sawn timber recovered from logs has a large influence on the profitability of a sawmill. The positioning of the log as it is fed into the primary breakdown saw is one of the factors that impacts on the volume recovery percentage. The log’s position can be adjusted by changes in rotation, offset and skewness and depending on the ranges and increments used for these variables, the number of possible combinations can become substantial. In a sawmill the time available to assess possible log positions is limited and different strategies can be followed to arrive at an optimal or close‐to‐optimal positioning solution without an exhaustive evaluation of solutions. Meta‐heuristics are sometimes used to arrive at solutions for combinatorial optimisation problems in a limited time. The effectiveness of this approach on the optimisation of timber volume recovery based on log form is evaluated in this study using sawmill simulation data of sixty SA pine logs. A new meta‐heuristic, for convenience named the Tentacle algorithm, was developed specifically for the problem of log positioning optimisation. The results obtained with the Tentacle algorithm was compared with results from three existing meta‐heuristics i.e. the Simulated Annealing algorithm, the Population Based Incremental Learning algorithm and the Particle Swarm Optimisation algorithm, in terms of its efficiency and effectiveness in finding good log positioning solutions in a limited time. A fifth method, that of exhaustively searching smaller, high quality areas around the centered and “horns‐up” and “horns‐down” positions in the search space was compared to that of using the meta‐heuristic algorithms. In terms of volume recovery, the Tentacle algorithm performed, on average, the best of the four algorithms evaluated. However, exhaustive searches in the smaller, high quality areas in the search space, outperformed the algorithms.
AFRIKAANSE OPSOMMING: Die herwinningspersentasie van gesaagde planke uit saagblokke het ‘n groot invloed op die winsgewendheid van ‘n saagmeul. Die posisionering van die blok in die primêre saag is een van die faktore wat die herwinningspersentasie beïnvloed. Die blok se posisie kan verstel word deur veranderinge in rotasie, oplyning en skeefheid. Afhangend van die veld ‐en inkrementgrootte kan die hoeveelheid moontlike kombinasies beduidend wees. In ‘n tipiese saagmeul is die beskikbare tyd om moontlike posisies te evalueer beperk en verskeie strategieë kan gevolg word om optimale of nabyoptimale kombinasies te bereik sonder om alle moontlike kombinasies te evalueer. Meta‐heuristieke word soms gebruik om in ‘n beperkte tyd oplossings te vind vir kombinatoriese optimeringsprobleme. Die doeltreffendheid van hierdie metode by die optimering van herwinningspersentasie gebaseer op blokvorm is in hierdie studie ondersoek. Dit is met behulp van saagmeulsimulasiedata soos van sestig SA dennehoutblokke verkry, uitgevoer. ‘n Nuwe meta‐heuristiek, genaamd die Tentakelalgoritme, is tydens hierdie studie spesifiek vir die probleem van blokposisie‐optimering ontwikkel. Die resultate verkry met die Tentakelalgoritme is vergelyk met drie bestaande meta‐heuristieke, nl. die “Simulated Annealing”‐algoritme, die “Population Based Incremental Learning”‐algoritme en die “Particle Swarm Optimisation”‐algoritme in terme van doeltreffendheid om goeie blokposisies in ‘n beperkte tyd te vind. ‘n Vyfde metode, die gebruik van ‘n volledige ondersoek van verkleinde versamelings, rondom hoë‐kwaliteit areas in die soekarea, is vergelyk met die gebruik van die meta‐heuristieke. Hierdie hoë‐kwaliteit areas word gevind rondom die gesentreerde “horns‐up” en “horns‐down” posisies. Die Tentakelalgoritme het gemiddelde die beste herwinningsresultate van die vier meta‐heuristieke wat ondersoek was gelewer. Die volledige ondersoek van verkleinde versamelings in die hoë kwaliteit areas het egter die meta‐heuristieke oortref.
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21

Wong, Andy King-sing. "Optimisation of container process at multimodal container terminals". Thesis, Queensland University of Technology, 2008. https://eprints.qut.edu.au/16626/1/Andy_Wong_Thesis.pdf.

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Multimodal container terminals are an important part of the logistics systems in international trade. Any improvement in the terminal efficiency is likely to reduce the costs of transporting goods, and to strengthen the trading position of the nation. During the import process, containers flow from ships to the storage yard for temporary storage and then are later moved to the hinterland by rail, or by road. The export process is the reverse of the import process. From the marshalling area, it is possible for a yard machine to carry an inbound container to the storage area and back with an inbound container in one round trip. This thesis investigates the inbound and outbound container process of multimodal container terminals in a multi-ship and multi-berth environment. The aim is to develop mathematical models and analytical tools for yard operation and planning. This study concerns the yardlayout, storage locations, operation strategies as well as the sequencing and scheduling of container process. Several models are developed for the scheduling of container process, taking account of planned and unplanned disruptions, and the intermediate buffer at the marshalling area. The problem is NP-hard and real-life problems often involve large number of containers. In addition, many schedules may not be feasible due to deadlock or violation of precedence-constraints. Good results were achieved on benchmark problems using the proposed innovative. In dealing with unplanned disruptions, reactive scheduling approach was found to give the results similar to as if the disruptions were planned in advance. Numerical investigations are also presented on various factors affecting the efficiency of seaport container terminals including the number of yard machines, and the number of quay crane. As with the various yard-layouts studied, it was found that containers are best stored in rows perpendicular to the quay-line with about 10 to 14 bays in each row. For a shorter ship service time, ideally the containers should be stored as close as possible to the ship. The best storage locations, however, are scarce resources and are not always available. Another model is developed for the best storage location as well as the best schedule for the container process. From an initial best schedule with predefined storage locations, the problem is solved by iterating through the refinement of storage scheme and re-scheduling. At a seaport terminal, ships are planned to arrive and leave within a scheduled time window. Nevertheless, a ship may arrive late due to poor weather conditions or disruptions at the previous port. Such delay may also affect its departure to the subsequent port. To minimise the impact of ship delays, port operators must consider alternate arrangements including re-assignment of berths, re-sequencing of ships and rescheduling of the container process. A ship delay model is developed and the problem is solved by combining branching and Tabu Search. The models developed in this thesis establish the relationship between significant factors and the options for increasing throughput by discovering the bottlenecks. The models are applicable as decision tools for operation planning, yard layout, and cost and benefit analysis for investment in infrastructures.
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22

Wong, Andy King-sing. "Optimisation of container process at multimodal container terminals". Queensland University of Technology, 2008. http://eprints.qut.edu.au/16626/.

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Multimodal container terminals are an important part of the logistics systems in international trade. Any improvement in the terminal efficiency is likely to reduce the costs of transporting goods, and to strengthen the trading position of the nation. During the import process, containers flow from ships to the storage yard for temporary storage and then are later moved to the hinterland by rail, or by road. The export process is the reverse of the import process. From the marshalling area, it is possible for a yard machine to carry an inbound container to the storage area and back with an inbound container in one round trip. This thesis investigates the inbound and outbound container process of multimodal container terminals in a multi-ship and multi-berth environment. The aim is to develop mathematical models and analytical tools for yard operation and planning. This study concerns the yardlayout, storage locations, operation strategies as well as the sequencing and scheduling of container process. Several models are developed for the scheduling of container process, taking account of planned and unplanned disruptions, and the intermediate buffer at the marshalling area. The problem is NP-hard and real-life problems often involve large number of containers. In addition, many schedules may not be feasible due to deadlock or violation of precedence-constraints. Good results were achieved on benchmark problems using the proposed innovative. In dealing with unplanned disruptions, reactive scheduling approach was found to give the results similar to as if the disruptions were planned in advance. Numerical investigations are also presented on various factors affecting the efficiency of seaport container terminals including the number of yard machines, and the number of quay crane. As with the various yard-layouts studied, it was found that containers are best stored in rows perpendicular to the quay-line with about 10 to 14 bays in each row. For a shorter ship service time, ideally the containers should be stored as close as possible to the ship. The best storage locations, however, are scarce resources and are not always available. Another model is developed for the best storage location as well as the best schedule for the container process. From an initial best schedule with predefined storage locations, the problem is solved by iterating through the refinement of storage scheme and re-scheduling. At a seaport terminal, ships are planned to arrive and leave within a scheduled time window. Nevertheless, a ship may arrive late due to poor weather conditions or disruptions at the previous port. Such delay may also affect its departure to the subsequent port. To minimise the impact of ship delays, port operators must consider alternate arrangements including re-assignment of berths, re-sequencing of ships and rescheduling of the container process. A ship delay model is developed and the problem is solved by combining branching and Tabu Search. The models developed in this thesis establish the relationship between significant factors and the options for increasing throughput by discovering the bottlenecks. The models are applicable as decision tools for operation planning, yard layout, and cost and benefit analysis for investment in infrastructures.
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23

Kanda, Jorge Yoshio. "Uso de meta-aprendizado na recomendação de meta-heurísticas para o problema do caixeiro viajante". Universidade de São Paulo, 2012. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-19022013-142839/.

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O problema do caixeiro viajante (PCV) é um problema clássico de otimização que possui diversas variações, aplicações e instâncias. Encontrar a solução ótima para muitas instâncias desse problema é geralmente muito difícil devido o alto custo computacional. Vários métodos de otimização, conhecidos como meta-heurísticas (MHs), são capazes de encontrar boas soluções para o PCV. Muitos algoritmos baseados em diversas MHs têm sido propostos e investigados para diferentes variações do PCV. Como não existe um algoritmo universal que encontre a melhor solução para todas as instâncias de um problema, diferentes MHs podem prover a melhor solução para diferentes instâncias do PCV. Desse modo, a seleção a priori da MH que produza a melhor solução para uma dada instância é uma tarefa difícil. A pesquisa desenvolvida nesta tese investiga o uso de abordagens de meta-aprendizado para selecionar as MHs mais promissoras para novas instâncias de PCV. Essas abordagens induzem meta-modelos preditivos a partir do treinamento das técnicas de aprendizado de máquina em um conjunto de meta-dados. Cada meta-exemplo, em nosso conjunto de meta-dados, representa uma instância de PCV descrita por características (meta-atributos) do PCV e pelo desempenho das MHs (meta-atributo alvo) para essa instância. Os meta-modelos induzidos são usados para indicar os valores do meta-atributo alvo para novas instâncias do PCV. Vários experimentos foram realizados durante a investigação desta pesquisa e resultados importantes foram obtidos
The traveling salesman problem (TSP) is a classical optimization problem that has several variations, applications and instances. To find the optimal solution for many instances of this problem is usually a very hard task due to high computational cost. Various optimization methods, known as metaheuristics (MHs), are capable to generate good solutions for the TSP. Many algorithms based on different MHs have been proposed and investigated for different variations of the TSP. Different MHs can provide the best optimization solution for different TSP instances, since there is no a universal algorithm able to find the best solution for all instances. Thus, a priori selection of the MH that produces the best solution for a given instance is a hard task. The research developed in this thesis investigates the use of meta-learning approaches to select the most promising MHs for new TSP instances. These approaches induce predictive meta-models from the training of machine learning techniques on a set of meta-data. In our meta-data, each meta-example is a TSP instance described by problem characteristics (meta-features) and performance of MHs (target meta-features) for this instance. The induced meta-models are used to indicate the values of the target meta-feature for new TSP instances. During the investigation of this research, several experiments were performed and important results were obtained
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24

De, Souza Bento Da Silva Pedro Paulo. "On the mapping of distributed applications onto multiple Clouds". Thesis, Lyon, 2017. http://www.theses.fr/2017LYSEN089/document.

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Le Cloud est devenu une plate-forme très répandue pour le déploiement d'applications distribuées. Beaucoup d'entreprises peuvent sous-traiter leurs infrastructures d'hébergement et, ainsi, éviter des dépenses provenant d'investissements initiaux en infrastructure et de maintenance.Des petites et moyennes entreprises, en particulier, attirés par le modèle de coûts sur demande du Cloud, ont désormais accès à des fonctionnalités comme le passage à l'échelle, la disponibilité et la fiabilité, qui avant le Cloud étaient presque réservées à de grandes entreprises.Les services du Cloud peuvent être offerts aux utilisateurs de plusieurs façons. Dans cette thèse, nous nous concentrons sur le modèle d'Infrastructure sous Forme de Service. Ce modèle permet aux utilisateurs d’accéder à des ressources de calcul virtualisés sous forme de machine virtuelles (MVs).Pour installer une application distribuée, un client du Cloud doit d'abord définir l'association entre son application et l'infrastructure. Il est nécessaire de prendre en considération des contraintesde coût, de ressource et de communication pour pouvoir choisir un ensemble de MVs provenant d'opérateurs de Cloud publiques et privés le plus adaptés. Cependant, étant donné la quantité exponentiel de configurations, la définition manuelle de l'association entre application et infrastructure peut être un challenge dans des scénarios à large échelle ou ayant des contraintes importantes de temps. En effet, ce problème est une généralisation du problème de calcul de homomorphisme de graphes, qui est NP-complet.Dans cette thèse, nous adressons le problème de calculer des placements initiaux et de reconfiguration pour des applications distribuées sur potentiellement de multiples Clouds. L'objectif est de minimiser les coûts de location et de migration en satisfaisant des contraintes de ressources et communications. Pour cela, nous proposons des heuristiques performantes capables de calculer des placements de bonne qualité très rapidement pour des scénarios à petite et large échelles. Ces heuristiques, qui sont basées sur des algorithmes de partition de graphes et de vector packing, ont été évaluées en les comparant avec des approches de l'état de l'art comme des solveurs exactes et des méta-heuristiques. Nous montrons en utilisant des simulations que les heuristiques proposées arrivent à calculer des solutions de bonne qualité en quelques secondes tandis que des autres approches prennent des heures ou jours pour les calculer
The Cloud has become a very popular platform for deploying distributed applications. Today, virtually any credit card holder can have access to Cloud services. There are many different ways of offering Cloud services to customers. In this thesis we especially focus on theInfrastructure as a Service (IaaS), a model that, usually, proposes virtualized computing resources to costumers in the form of virtual machines (VMs). Thanks to its attractive pay-as-you-use cost model, it is easier for customers, specially small and medium companies, to outsource hosting infrastructures and benefit of savings related to upfront investments and maintenance costs. Also, customers can have access to features such as scalability, availability, and reliability, which previously were almost exclusive for large companies. To deploy a distributed application, a Cloud customer must first consider the mapping between her application (or its parts) to the target infrastructure. She needs to take into consideration cost, resource, and communication constraints to select the most suitable set of VMs, from private and public Cloud providers. However, defining a mapping manually may be a challenge in large-scale or time constrained scenarios since the number of possible configuration explodes. Furthermore, when automating this process, scalability issues must be taken into account given that this mapping problem is a generalization of the graph homomorphism problem, which is NP-complete.In this thesis we address the problem of calculating initial and reconfiguration placements for distributed applications over possibly multiple Clouds. Our objective is to minimize renting and migration costs while satisfying applications' resource and communication constraints. We concentrate on the mapping between applications and Cloud infrastructure. Using an incremental approach, we split the problem into three different parts and propose efficient heuristics that can compute good quality placements very quickly for small and large scenarios. These heuristics are based on graph partition and vector packing heuristics and have been extensively evaluated against state of the art approaches such as MIP solvers and meta-heuristics. We show through simulations that the proposed heuristics manage to compute solutions in a few seconds that would take many hours or days for other approaches to compute
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25

Kaja, Sai Chandana. "A New Approach for Solving the Disruption in Vehicle Routing Problem During the Delivery : A Comparative Analysis of VRP Meta-Heuristics". Thesis, Blekinge Tekniska Högskola, Institutionen för datavetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-19576.

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Context. The purpose of this research paper is to describe a new approach for solving the disruption in the vehicle routing problem (DVRP) which deals with the disturbance that will occur unexpectedly within the distribution area when executing the original VRP plan. The paper then focuses further on the foremost common and usual problem in real-time scenarios i.e., vehicle-breakdown part. Therefore, the research needs to be accomplished to deal with these major disruption in routing problems in transportation. Objectives. The study first investigates to find suitable and efficient metaheuristic techniques for solving real-time vehicle routing problems than an experiment is performed with the chosen algorithms which might produce near-optimal solutions. Evaluate the performance of those selected algorithms and compare the results among each other. Methods. To answer research questions, firstly, a literature review has been performed to search out suitable meta-heuristic techniques for solving vehicle routing problems. Then based on the findings an experiment is performed to evaluate the performance of selected meta-heuristic algorithms. Results. Results from the literature review showed that the meta-heuristic approaches such as. Tabu Search, Ant Colony Optimization, and Genetic Algorithmare suitable and efficient algorithms for solving real-time vehicle routing problems. The performance of those algorithms has been calculated and compared with one another with standard benchmarks. Conclusions. The performance of a Tabu Search algorithm is best among the other algorithms, followed by Ant Colony Optimization and Genetic Algorithm. Therefore, it has been concluded that the Tabu Search is the best algorithm for solving real-time disruption problems in VRP. The results are similar to the performance comparison of the selected algorithms and standard benchmarks are presented within the research.
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Luche, José Roberto Dale. "Modelos e algoritmos para a otimização do planejamento da produção de grãos eletrofundidos". Universidade Federal de São Carlos, 2011. https://repositorio.ufscar.br/handle/ufscar/3396.

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Made available in DSpace on 2016-06-02T19:50:15Z (GMT). No. of bitstreams: 1 4224.pdf: 4088163 bytes, checksum: f36f82cf58386b4174743eccaa446df4 (MD5) Previous issue date: 2011-02-12
The number of successful applications that use optimization models has followed the evolution of the computers, as much in hardware, with more powerful machines, as in software, with more intelligent algorithms. Due to importance of the modeling as a decision support tool, much effort has been made to mathematically describe systems of interest and devise techniques for solving such models. This work presents a detailed description of the operations involved in production planning and control of the electrofused grain industry and proposes the use of exact and heuristic methods to support decisions in such activities, particularly in production scheduling. Several visits were made to companies in this sector and a case study was carried out one of these companies in order to formulate alternatives to increase productivity and improve customer service. Optimizing the production scheduling of electrofused grains is not a simple task mainly because of the scale of the equipment setup times, the diversity of the products, and the narrow orders due dates. Based on the case study, mixed linear programming models that combine known models of process selection and single-stage lot sizing were developed, and a constructive heuristic, local search variants, and a GRASP algorithm were proposed to solve one of the models. Computational results with a real instance and randomly generated instance sets show that the exact methods as well as the heuristics can produce as good or better production scheduling than the ones currently employed by the studied company
O número de aplicações bem sucedidas que utilizam modelos de otimização têm acompanhado a evolução dos computadores, tanto em hardware, com máquinas mais poderosas, como em software, com algoritmos mais inteligentes. Devido à importância da modelagem como ferramenta de apoio à tomada de decisão, muitos trabalhos que exploram formas de representação de problemas e técnicas de solução de modelos vêm sendo desenvolvidos. Este trabalho apresenta uma descrição detalhada das operações envolvidas no planejamento e controle da produção na indústria de grãos eletrofundidos e propõe o uso de modelos e métodos exatos e heurísticos para apoio à tomada de decisões nesta atividade, em particular, na programação da produção. Várias visitas foram realizadas a empresas do setor, e em uma dessas empresas foi empreendido um estudo de caso com o objetivo de formular alternativas para aumento da produtividade e a melhoria do nível de serviço aos clientes. Otimizar a programação da produção de grãos eletrofundidos não é uma tarefa simples, principalmente devido à grandeza dos tempos de preparação dos equipamentos, à diversidade de produtos e às limitações dos prazos de entrega da carteira de pedidos. Com base no estudo de caso, modelos de programação linear inteira mista que combinam modelos clássicos de seleção de processos e dimensionamento de lotes monoestágio foram desenvolvidos, e uma heurística construtiva, duas variantes de busca local, e um algoritmo GRASP foram propostos para resolver um dos modelos. Resultados computacionais com uma instância real e conjuntos de instâncias geradas aleatoriamente indicam que tanto os métodos exatos como heurísticos propostos são capazes de gerar programações da produção tão boas ou melhores do que as atualmente empregadas pela empresa estudada
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Diaz, Leiva Juan Esteban. "Simulation-based optimization for production planning : integrating meta-heuristics, simulation and exact techniques to address the uncertainty and complexity of manufacturing systems". Thesis, University of Manchester, 2016. https://www.research.manchester.ac.uk/portal/en/theses/simulationbased-optimization-for-production-planning-integrating-metaheuristics-simulation-and-exact-techniques-to-address-the-uncertainty-and-complexity-of-manufacturing-systems(9ef8cb33-99ba-4eb7-aa06-67c9271a50d0).html.

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This doctoral thesis investigates the application of simulation-based optimization (SBO) as an alternative to conventional optimization techniques when the inherent uncertainty and complex features of real manufacturing systems need to be considered. Inspired by a real-world production planning setting, we provide a general formulation of the situation as an extended knapsack problem. We proceed by proposing a solution approach based on single and multi-objective SBO models, which use simulation to capture the uncertainty and complexity of the manufacturing system and employ meta-heuristic optimizers to search for near-optimal solutions. Moreover, we consider the design of matheuristic approaches that combine the advantages of population-based meta-heuristics with mathematical programming techniques. More specifically, we consider the integration of mathematical programming techniques during the initialization stage of the single and multi-objective approaches as well as during the actual search process. Using data collected from a manufacturing company, we provide evidence for the advantages of our approaches over conventional methods (integer linear programming and chance-constrained programming) and highlight the synergies resulting from the combination of simulation, meta-heuristics and mathematical programming methods. In the context of the same real-world problem, we also analyse different single and multi-objective SBO models for robust optimization. We demonstrate that the choice of robustness measure and the sample size used during fitness evaluation are crucial considerations in designing an effective multi-objective model.
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Chuah, Keng Hoo. "OPTIMIZATION AND SIMULATION OF JUST-IN-TIME SUPPLY PICKUP AND DELIVERY SYSTEMS". UKnowledge, 2004. http://uknowledge.uky.edu/gradschool_diss/384.

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A just-in-time supply pickup and delivery system (JSS) manages the logistic operations between a manufacturing plant and its suppliers by controlling the sequence, timing, and frequency of container pickups and parts deliveries, thereby coordinating internal conveyance, external conveyance, and the operation of cross-docking facilities. The system is important to just-in-time production lines that maintain small inventories. This research studies the logistics, supply chain, and production control of JSS. First, a new meta-heuristics approach (taboo search) is developed to solve a general frequency routing (GFR) problem that has been formulated in this dissertation with five types of constraints: flow, space, load, time, and heijunka. Also, a formulation for cross-dock routing (CDR) has been created and solved. Second, seven issues concerning the structure of JSS systems that employ the previously studied common frequency routing (CFR) problem (Chuah and Yingling, in press) are explored to understand their impacts on operational costs of the system. Finally, a discreteevent simulation model is developed to study JSS by looking at different types of variations in demand and studying their impacts on the stability of inventory levels in the system. The results show that GFR routes at high frequencies do not have common frequencies in the solution. There are some common frequencies at medium frequencies and none at low frequency, where effectively the problem is simply a vehicle routing problem (VRP) with time windows. CDR is an extension of VRP-type problems that can be solved quickly with meta-heuristic approaches. GFR, CDR, and CFR are practical routing strategies for JSS with taboo search or other types of meta-heuristics as solvers. By comparing GFR and CFR solutions to the same problems, it is shown that the impacts of CFR restrictions on cost are minimal and in many cases so small as to make simplier CFR routes desirable. The studies of JSS structural features on the operating costs of JSS systems under the assumption of CFR routes yielded interesting results. First, when suppliers are clustered, the routes become more efficient at mid-level, but not high or low, frequencies. Second, the cost increases with the number of suppliers. Third, negotiating broad time windows with suppliers is important for cost control in JSS systems. Fourth, an increase or decrease in production volumes uniformly shifts the solutions cost versus frequency curve. Fifth, increased vehicle capacity is important in reducing costs at low and medium frequencies but far less important at high frequencies. Lastly, load distributions among the suppliers are not important determinants of transportation costs as long as the average loads remain the same. Finally, a one-supplier, one-part-source simulation model shows that the systems inventory level tends to be sticky to the reordering level. JSS is very stable, but it requires reliable transportation to perform well. The impact to changes in kanban levels (e.g., as might occur between route planning intervals when production rates are adjusted) is relatively long term with dynamic after-effects on inventory levels that take a long time to dissapate. A gradual change in kanban levels may be introduced, prior to the changeover, to counter this effect.
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29

Nnene, Obiora Amamifechukwu. "Simulation-based optimisation of public transport networks". Doctoral thesis, Faculty of Engineering and the Built Environment, 2020. http://hdl.handle.net/11427/32308.

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Public transport network design deals with finding the most efficient network solution among a set of alternatives, that best satisfies the often-conflicting objectives of different network stakeholders like passengers and operators. Simulation-based Optimisation (SBO) is a discipline that solves optimisation problems by combining simulation and optimisation models. The former is used to evaluate the alternative solutions, while the latter searches for the optimal solution among them. A SBO model for designing public transport networks is developed in this dissertation. The context of the research is the MyCiTi Bus Rapid Transit (BRT) network in the City of Cape Town, South Africa. A multi-objective optimisation algorithm known as the Non-dominated Sorting Genetic Algorithm (NSGA-II) is integrated with Activity-based Travel Demand Model (ABTDM) known as the Multi-Agent Transport Simulation (MATSim). The steps taken to achieve the research objectives are first to generate a set of feasible network alternatives. This is achieved by manipulating the existing routes of the MyCiTi BRT with a computer based heuristic algorithm. The process is guided by feasibility conditions which guarantee that each network has routes that are acceptable for public transport operations. MATSim is then used to evaluate the generated alternatives, by simulating the daily plans of travellers on each network. A typical daily plan is a sequential ordering of all the trips made by a commuter within a day. Automated Fare Collection (AFC) data from the MyCiTi BRT was used to create this plan. Lastly, the NSGA-II is used to search for an efficient set of network solutions, also known as a Pareto set or a non-dominated set in the context of Multi-objective Optimisation (MOO). In each generation of the optimisation process, MATSim is used to evaluate the current solution. Hence a suitable encoding scheme is defined to enable a smooth iv translation of the solution between the NSGA-II and MATSim. Since the solution of multi-objective optimisation problems is a set of network solutions, further analysis is done to identify the best compromise solution in the Pareto set. Extensive computational testing of the SBO model has been carried out. The tests involve evaluating the computational performance of the model. The first test measures the repeatability of the model's result. The second computational test considers its performance relative to indicators like the hypervolume and spacing indicators as well as an analysis of the model's Pareto front. Lastly, a benchmarking of the model's performance when compared with other optimisation algorithms is carried out. After testing the so-called Simulation-based Transit Network Design Model (SBTNDM), it is then used to design pubic transport networks for the MyCiTi BRT. Two applications are considered for the model. The first application deals with the public transport performance of the network solutions in the Pareto front obtained from the SBTNDM. In this case study, different transport network indicators are used to measure how each solution performs. In the second scenario, network design is done for the 85th percentile of travel demand on the MyCiTi network over 12 months. The results show that the model can design robust transit networks. The use of simulation as the agency of optimisation of public transport networks represents the main innovation of the work. The approach has not been used for public transport network design to date. The specific contribution of this work is in the improved modelling of public transport user behaviour with Agent-based Simulation (ABS) within a Transit Network Design (TND) framework. This is different from the conventional approaches used in the literature, where static trip-based travel demand models like the four-step model have mostly been used. Another contribution of the work is the development of a robust technique that facilitates the simultaneous optimisation of network routes and their operational frequencies. Future endeavours will focus on extending the network design model to a multi-modal context.
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30

Silva, Odilon Novaes. "Novas estratégias de implementação da meta-heurística VNS aplicada na otimização de grade horária /". Ilha Solteira, 2019. http://hdl.handle.net/11449/181984.

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Orientador: Rubén Augusto Romero Lázaro
Resumo: Neste projeto de pesquisa, é abordado o problema otimização de grade horária. O tipo de problema de grade horária abordado é aquele que tem o enunciado e a estrutura de dados apresentado no site da Competição Internacional de Otimização do Problema de Grade Horária. Esse problema pode ser modelado como sendo um problema de Programação Linear Binária de grande porte. Entretanto, os solvers comerciais disponíveis, como o CPLEX, não tem a capacidade de encontrar as soluções ótimas das 20 instâncias mostradas no site da Competição Internacional de Otimização do Problema de Grade Horária. Neste trabalho foi desenvolvido um algoritmo VNS especializado para resolver o problema de otimização de grade horária. A parcela inovadora da proposta está relacionado com o uso da lógica de partição para encontrar a melhor solução vizinha da solução corrente de forma eficiente e para uma estrutura de vizinhança complexa e formada por muitos elementos. Dessa forma, a proposta de otimização se tornou muito eficiente na resolução das 20 instâncias cujos dados se encontram no site da Competição Internacional de Otimização do Problema de Grade Horária.
Abstract: In this research project, we address the optimization timetabling problem. The type of timetabling problem addressed is one that has the statement and data structure displayed on the site of the International Competition of Optimization of the Timetabling Problem. This problem can be modeled as a large Binary Linear Programming Problem. However, the commercial solvers available, such as CPLEX, do not have the ability to nd the optimal solutions from the 20 instances shown on the site of the International Competition of Optimization of the timetabling Problem. In this work a specialized VNS algorithm was developed to solve the optimization of Timetabling Problem . The innovative part of the proposal is related to the use of partition logic to nd the best neighborhood solution of the current solution e ciently and to a structure of complex neighborhood formed by many elements. In this way, the optimization proposal became very e cient in the resolution of the 20 instances whose data were found on the website of the International Competition for Optimization of the Timetabling Problem.
Doutor
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31

Erskine, Adam. "Analysis of behaviours in swarm systems". Thesis, University of Edinburgh, 2016. http://hdl.handle.net/1842/20413.

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In nature animal species often exist in groups. We talk of insect swarms, flocks of birds, packs of lions, herds of wildebeest etc. These are characterised by individuals interacting by following their own rules, privy only to local information. Robotic swarms or simulations can be used explore such interactions. Mathematical formulations can be constructed that encode similar ideas and allow us to explore the emergent group behaviours. Some behaviours show characteristics reminiscent of the phenomena of criticality. A bird flock may show near instantaneous collective shifts in direction: velocity changes that appear to correlated over distances much larger individual separations. Here we examine swarm systems inspired by flocks of birds and the role played by criticality. The first system, Particle Swarm Optimisation (PSO), is shown to behave optimally when operating close to criticality. The presence of a critical point in the algorithm’s operation is shown to derive from the swarm’s properties as a random dynamical system. Empirical results demonstrate that the optimality lies on or near this point. A modified PSO algorithm is presented which uses measures of the swarm’s diversity as a feedback signal to adjust the behaviour of the swarm. This achieves a statistically balanced mixture of exploration and exploitation behaviours in the resultant swarm. The problems of stagnation and parameter tuning often encountered in PSO are automatically avoided. The second system, Swarm Chemistry, consists of heterogeneous particles combined with kinetic update rules. It is known that, depending upon the parametric configuration, numerous structures visually reminiscent of biological forms are found in this system. The parameter set discovered here results in a cell-division-like behaviour (in the sense of prokaryotic fission). Extensions to the swarm system produces a swarm that shows repeated cell division. As such, this model demonstrates a behaviour of interest to theories regarding the origin of life.
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32

Zhao, Xiagang. "Algorithmes pour les problèmes de tournées à la demande". Phd thesis, Université Blaise Pascal - Clermont-Ferrand II, 2011. http://tel.archives-ouvertes.fr/tel-00671350.

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Dans le cadre de cette thèse, nous nous intéressons au problème du transport à la demande. Nous proposons des heuristiques pour résoudre ce problème de manière rapide et efficace. Dans cette thèse, nous traitons trois problèmes : le premier est le Dial-a-ride (DARP standard). Pour ce problème, nous proposons des heuristiques basées sur la technique d'insertion et une technique de propagation de contrainte. Nous proposons aussi la procédure SPLIT et des opérateurs classiques de recherche locale pour résoudre ce problème. Le second est le DARP multicritères pour laquelle nous proposons un schéma de type ELS. Le troisième est un problème de transport à la demande avec contraintes financières (DARPF), qui est une extension de DARP. Nous résolvons ce problème grâce à une heuristique d'insertion et une technique de propagation de contraintes. La fonction objectif détermine les caractéristiques des tournées. Des résultats expérimentaux montrent que nos (méta-) heuristiques donnent des résultats plus favorables aux clients (meilleure qualité de service)
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33

Rouky, Naoufal. "Optimisation et simulation de la massification du transport multimodal de conteneurs". Thesis, Normandie, 2018. http://www.theses.fr/2018NORMLH40/document.

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Les ports maritimes se confrontent à des exigences rigoureuses imposées par l'évolution de la taille de la flotte mondiale des porte-conteneurs et des zones de stockage qui arrivent à des niveaux de saturation élevés. Pour répondre à ces défis, plusieurs ports ont décidé de créer des terminaux multimodaux qui jouent le rôle de méga-hubs pour les terminaux maritimes, en vue de libérer les zones de stockage de ces terminaux, de développer la part du transport massifié de conteneurs et de réduire les émissions des gaz à effet de serre en utilisant des modes alternatifs à la route. Néanmoins, la gestion de ces nouveaux schémas logistiques est laborieuse. Cela s’explique par plusieurs facteurs, entre autres, la nature dynamique et distribuée de ces systèmes, la diversité des opérations et le manque des informations nécessaires au contrôle de flux. La finalité de cette thèse est de développer des approches capables de répondre aux besoins des opérateurs portuaires dans un terminal multimodal, avec prise en compte des différentes sources d’incertitudes. Deux problèmes d'optimisation sont principalement considérés dans cette thèse, à savoir : l'optimisation de tournées de navettes ferroviaires (The Rail Shuttle Routing Problem) et l'ordonnancement de grues de quai (The Quay Crane Scheduling Problem). En vue d'aborder la complexité et l’aspect incertain de ces problèmes, nous proposerons des modélisations mathématiques, ainsi que des approches de résolution basées sur l’optimisation par colonies de fourmis, l’optimisation robuste et le couplage Simulation-Optimisation. Les différents tests numériques effectués ont prouvé l’efficacité des algorithmes proposés et leur robustesse
Today, seaports face increasingly stringent requirements imposed by the considerable growth of goods transited by sea. Indeed, the organization of the port sector has evolved rapidly and has caused several negative impacts, including pollution and congestion of terminals, which constitute today the major concerns of port operators. To address those challenges, several ports have decided to build multimodal terminals that act as mega-hubs for maritime terminals, in order to free the storage areas on the maritime terminals, to promote the use of consolidated container modes of transfer and to reduce greenhouse gas emissions by using alternative modes to the road. Nevertheless, the management of these new logistic systems is laborious. This is due to several factors, including the dynamic and distributed nature of these systems, the variety of operations, and the lack of information needed to control flow. The aim of this thesis is to develop approaches capable of meeting the needs of port operators in a multimodal terminal, taking into account the different sources of uncertainty. Two optimization problems are mainly considered in this thesis, namely : the Rail Shuttle Routing Problem(RSRP) and the Quay Crane Scheduling Problem(QCSP). To address the complexity and uncertainties of these problems, we propose new mathematical models, as well as some heuristics approaches based on ant colony optimization, robust optimization and Simulation-Optimization. The various numerical tests carried out proved the effectiveness and the robustness of the proposed algorithms
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Frascati, Giuliano. "Programação da produção em máquina única com setup dependente da sequência e terceirização permitida: uma abordagem de otimização por colônia de formigas". Universidade Federal de São Carlos, 2014. https://repositorio.ufscar.br/handle/ufscar/3745.

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Financiadora de Estudos e Projetos
Many scheduling problems found in the literature are classified as NP-Hard, which means that the computational costs of the solutions within known exact mathematical methods can be very time consuming. In the case of partial outsourcing it is essential to consider the outsourcing decisions inside the scheduling problem to achieve optimal results from outsourcing. This project discusses the following issue: a single machine environment where the setup times are sequence-dependent and there is an outsourcing option. The goal is to determinate the set of jobs that will be outsourced and the production sequence of the jobs that will be performed inhouse, aiming to eliminate the total tardiness of all jobs, witch is a NP-Had problem. New approaches regarding meta-heuristics, like ACO (Ant Colony Optimization) show a new horizon for this kind of issues. The hybrid algorithm, including ACO and local search methods, reached the optimal values in 94,7% of the problems.
Diversos problemas de scheduling são classificados na literatura como NP-Difíceis, o que significa que os custos computacionais das soluções desenvolvidas usando métodos exatos conhecidos são muito altos para esses problemas. No caso da possibilidade de terceirização de parte das tarefas existentes se torna vital inserir essas decisões nos problemas de scheduling visando à obtenção de resultados ótimos para os objetivos de desempenho. O presente trabalho trata de um caso como esse: um ambiente de máquina única onde os tempos de setup são dependentes da sequência de execução das operações e com a possibilidade de terceirização. O objetivo é determinar a sequência de operações executadas no ambiente de máquina única e o conjunto de operações a serem terceirizadas de forma que nenhuma das ordens de serviço seja entregue com atraso e o custo de terceirização seja mínimo. A aplicação de meta-heurísticas, como o ACO (Ant Colony Optimization) abre um novo horizonte para o desenvolvimento de soluções para problemas este, classificado como NP-Difícil, sobretudo quando aplicadas em conjunto com métodos de busca local para o refinamento das soluções. Os resultados demontram que o algoritmo híbrido incluindo ACO e busca local, obteve resultados significativos, atingindo a resposta ótima em 94,7% dos problemas.
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35

Guden, Huseyin. "An Adaptive Simulated Annealing Method For Assembly Line Balancing And A Case Study". Master's thesis, METU, 2006. http://etd.lib.metu.edu.tr/upload/12607478/index.pdf.

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Assembly line balancing problem is one of the most studied NP-Hard problems. NP-Hardness leads us to search for a good solution instead of the optimal solution especially for the big-size problems. Meta-heuristic algorithms are the search methods which are developed to find good solutions to the big-size and combinatorial problems. In this study, it is aimed at solving the multi-objective multi-model assembly line balancing problem of a company. A meta-heuristic algorithm is developed to solve the deterministic assembly line balancing problems. The algorithm developed is tested using the test problems in the literature and the the real life problem of the company as well. The results are analyzed and found to be promising and a solution is proposed for the firm.
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36

Sucupira, Igor Ribeiro. "Um Estudo Empírico de Hiper-Heurísticas". Universidade de São Paulo, 2007. http://www.teses.usp.br/teses/disponiveis/45/45134/tde-15012008-001809/.

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Uma hiper-heurística é uma heurística que pode ser utilizada para lidar com qualquer problema de otimização, desde que a ela sejam fornecidos alguns parâmetros, como estruturas e abstrações, relacionados ao problema considerado. As hiper-heurísticas têm sido aplicadas a alguns problemas práticos e apresentadas como métodos de grande potencial, no que diz respeito à capacidade de possibilitar o desenvolvimento, em tempo bastante reduzido, de algoritmos capazes de lidar satisfatoriamente, do ponto de vista prático, com problemas de otimização complexos e pouco conhecidos. No entanto, é difícil situar as hiper-heurísticas em algum nível de qualidade e avaliar a robustez dessas abordagens caso não as apliquemos a problemas para os quais existam diversas instâncias disponíveis publicamente e já experimentadas por algoritmos relevantes. Este trabalho procura dar alguns passos importantes rumo a essas avaliações, além de ampliar o conjunto das hiper-heurísticas, compreender o impacto de algumas alternativas naturais de desenvolvimento e estabelecer comparações entre os resultados obtidos por diferentes métodos, o que ainda nos permite confrontar as duas diferentes classes de hiper-heurísticas que identificamos. Com essas finalidades em mente, desenvolvemos 3 novas hiper-heurísticas e implementamos 2 das hiper-heurísticas mais importantes criadas por outros autores. Para estas últimas, experimentamos ainda algumas extensões e modificações. Os dois métodos hiper-heurísticos selecionados podem ser vistos como respectivos representantes de duas classes distintas, que aparentemente englobam todas as hiper-heurísticas já desenvolvidas e nos permitem denominar cada um desses métodos como \"hiper-heurística de busca direta por entornos\" ou como \"hiper-heurística evolutiva indireta\". Implementamos cada hiper-heurística como uma biblioteca (em linguagem C), de forma a evidenciar e estimular a independência entre o nível em que se encontra a hiper-heurística e aquele onde se apresentam as estruturas e abstrações diretamente relacionadas ao problema considerado. Naturalmente, essa separação é de ingente importância para possibilitar a reutilização imediata das hiper-heurísticas e garantir que nelas haja total ausência de informações relativas a um problema de otimização específico.
A hyperheuristic is a heuristic that can be used to handle any optimization problem, provided that the algorithm is fed with some parameters, as structures and abstractions, related to the problem at hand. Hyperheuristics have been applied to some practical problems and presented as methods with great potential to allow the quick development of algorithms that are able to successfully deal, from a practical standpoint, with complex ill-known optimization problems. However, it\'s difficult to position hyperheuristics at some quality level and evaluate their robustness without applying them to problems for which there are many instances available in the public domain and already attacked by worthy algorithms. This work aims to give some important steps towards that process of evaluation, additionally increasing the number of available hyperheuristics, studying the impact of some natural development alternatives and comparing the results obtained by different methods, what also enables us to confront the two classes of hyperheuristics that we have identified. With those purposes in mind, we have developed 3 original hyperheuristics and implemented 2 of the most important hyperheuristics created by other authors. For those latter two approaches, we have also experimented with some modifications and extensions. The two methods we have chosen for implementation may be seen as respectively representing two distinct classes, which seem to contain all hyperheuristics developed so far and that allow us to classify any of these methods as either being a \"direct neighbourhood search hyperheuristic\" or an \"indirect evolutive hyperheuristic\". We have implemented each hyperheuristic as a library (in the C language), so as to clearly show and estimulate the independence between the level where the hyperheuristic is and that to which the structures and abstractions directly related to the problem at hand belong. Obviously, this separation of concerns is extremely important to make the immediate reuse of hyperheuristics possible and enforce in them the complete absence of information from a specific optimization problem.
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37

Proto, Andréa Barboza [UNESP]. "Interface Gráfica para o planejamento da expansão da transmissão de energia elétrica". Universidade Estadual Paulista (UNESP), 2009. http://hdl.handle.net/11449/87084.

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Neste trabalho propõe-se o desenvolvimento de uma interface gráfica voltada para a resolução do problema de planejamento da expansão das linhas de transmissão, que utiliza-se de programas para a obtenção das soluções ótimas ou de boas soluções. A grande dificuldade encontrada por usuários ao interagir com estes programas, motivou o desenvolvimento de uma aplicação com interface gráfica, a qual disponibiliza ao usuário diversas metodologias para a resolução do problema do planejamento da expansão das linhas de transmissão de energia elétrica. Espera-se que software como este, agregado ao sistema de ensino tradicional que normalmente ´e utilizado num curso de engenharia elétrica, possa fortalecer o processo de aprendizagem do aluno. Assim, o software educacional Transmission Expansion Planning (TEP 1.0) está sendo desenvolvido visando propiciar um ambiente agradável para a realização de simulações e testes e favorecer a aprendizagem dos conceitos que envolvem o problema do planejamento da expansão da transmissão. É possível através deste software fazer simulações para os sistemas: Garver (6 barras/ 15 ramos), Sul brasileiro (46 barras/79 ramos) e Norte-Nordeste brasileiro (87 barras/179 ramos). O software se beneficia de recursos oferecidos por programas que são executados em background, bem como da utilização de meta-heurísticas e do ambiente de processamento de máquinas paralelas virtuais, as quais podem ser selecionadas para realização dos testes em determinado sistema
This work proposes the development of a computational tool aimed at solving the problem of the transmission expansion planning, which uses programs in the background to obtain optimal solutions or good solutions. The great difficulty for users to interact with these programs, motivated the development of an application with a graphical interface, which provides the user with various methodologies for solving the problem of expansion planning of transmission lines of electricity. It is expected that software like this, added to the traditional school system which is normally used in electrical engineering courses, can strengthen the process of student learning. Thus, the educational software Transmission Expansion Planning (TEP 1.0) is being developed to provide a pleasant environment for simulations and testing and promote the learning of concepts involving the issue of transmission expansion planning. It is possible using this software to do simulations for the systems: Garver (6 nodes / 15 branches), South Brazilian (46 nodes / 79 branches) and North-Northeast Brazilian (87 nodes / 179 branches). The software takes advantage of capabilities offered by programs that run on background, and using meta-heuristics and the processing environment, parallel virtual machine, which can be selected to test on a system
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Silva, Pedro Henrique González. "Metaheurística para o Problema de Planejamento de Redes de Transmissão de Energia Elétrica com Redimensionamento". Universidade do Estado do Rio de Janeiro, 2012. http://www.bdtd.uerj.br/tde_busca/arquivo.php?codArquivo=4552.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Com o passar do tempo, a demanda elétrica de diversas áreas varia tornando necessária a construção de novos geradores elétricos e a expansão da rede de transmissão de energia elétrica. Nesta dissertação, focamos no problema de expansão da rede de transmissão, assumindo que novos geradores estão construídos para suprir as novas demandas. Essa expansão exige altos investimentos que precisam ser cuidadosamente planejados. O problema pode ser modelado como um problema de otimização não linear inteira mista e pertence à classe dos problemas NP-difíceis. Desta forma, uma abordagem heurística pode ser adequada para a sua solução pois pode vir a fornecer boas soluções em tempo computacional aceitável. Esta dissertação se propõe a apresentar um estudo do problema de planejamento da expansão de redes de transmissão de energia elétrica estático e multiestágio. Mostramos o que já existe na literatura para o que é chamado de problema sem redimensionamento e as inovações feitas por nós para o problema com redimensionamento. Quanto aos métodos de solução, utilizamos a metaheurística GRASP para o problema estático e combinamos o GRASP com o procedimento Backward-Forward quando falamos em problema multiestágio. Nesta dissertação comparamos os resultados computacionais obtidos com resultados encontrados na literatura.
At times, the electrical load in diferent areas varies, claiming the construction of new electric generators and the expansion of the electrical transmission network. In this dissertation we focus on the transmission expansion planning problem, assuming that new generators are built to meet the new demands. This expansion requires large investments, which need to be carefully planned. This problem can be modeled as a mixed nonlinear programming problem, considered to be a NP-hard problem. Therefore a heuristic approach may be appropriate for its solution because it might be able to provide good solutions in satisfactory computational time. This dissertation intends to present a study of both the static and multistage transmission expansion planning problem. We present first a review of the most interesting works found in the technical literature. Then, we present metaheuristics for the static and multistage problems with re-design. These etaheuristics extend known algorithms for the problems without re-design. For the static problem, we extend a GRASP procedure and for the multistage problem, we embed the GRASP (or an exact method) into a backward-forward algorithm. We test our algorithms on real-based power transmission networks and compare them to the results found in the litterature.
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39

Luscombe, Ruth. "A dynamic real time scheduling methodology for the emergency department". Thesis, Queensland University of Technology, 2015. https://eprints.qut.edu.au/86505/1/Ruth_Luscombe_Thesis.pdf.

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This project constructs a scheduling solution for the Emergency Department. The schedules are generated in real-time to adapt to new patient arrivals and changing conditions. An integrated scheduling formulation assigns patients to beds and treatment tasks to resources. The schedule efficiency is assessed using waiting time and total care time experienced by patients. The solution algorithm incorporates dispatch rules, meta-heuristics and a new extended disjunctive graph formulation which provide high quality solutions in a fast time-frame for real time decision support. This algorithm can be implemented in an electronic patient management system to improve patient flow in the Emergency Department.
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40

Ben, Jemaa Abdelhak. "Coopération méta heuristique et logique floue pour le dimensionnement d'une installation hybride". Thesis, Reims, 2015. http://www.theses.fr/2015REIMS009/document.

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Cette thèse propose la méthodologie de dimensionnement optimal pour optimiser la configuration de système d'énergie hybride. Pour cela, nous utilisons une approche pour la génération de base de règles floues et une optimisation automatiques au moyen d'algorithme génétique et d'un PSO adaptés avec le floue. Ces algorithmes nous permet d'obtenir le nombre optimal de panneaux photovoltaïques, d'éoliennes et des batteries, minimisant le coût total du système et garantissant la disponibilité permanente de l'électricité pour couvrir les besoins énergétiques. L'historique horaire de vitesse du vent, d’ensoleillement, sont utilisés pour modéliser la production des éoliennes, la production photovoltaïque et de charge. Le coût total est la fonction objective et la taille technique est une contrainte
This thesis proposes the optimum sizing methodology to optimize the configuration of hybrid energy system. For this, we use an approach for automatic fuzzy rule base generation and optimization by means of Fuzzy-Adaptive Genetic Algorithm and fuzzy adaptive PSO. This Algorithms allows us to obtain the optimal number of photovoltaic panels, wind turbines and storages units, ensuring the minimal global high efficiency system total cost and guaranteeing the permanent availability of energy to cover the load energy requirements. Historical hourly wind speed, solar irradiance and load data are used to stochastically model the wind turbines, photovoltaic generation and load. The total cost is the objective function and the technical size is a constraint
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41

Dornelles, Arton Pereira. "A matheuristic approach for solving the high school timetabling problem". reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2015. http://hdl.handle.net/10183/140451.

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A geração de quadros de horários escolares é um problema clássico de otimização que tem sido largamente estudado devido a sua importâncias prática e teórica. O problema consiste em alocar um conjunto de aulas entre professor-turma em períodos de tempo pré-determinados, satisfazendo diferentes tipos de requisitos. Devido a natureza combinatória do problema, a resolução de instâncias médias e grandes torna-se uma tarefa desafiadora. Quando recursos são escassos, mesmo uma solução factível pode ser difícil de ser encontrada. Várias técnicas tem sido propostas na literatura científica para resolver o problema de geração de quadros de horários escolares, no entanto, métodos robustos ainda não existem. Visto que o uso de métodos exatos, como por exemplo, técnicas de programação matemática, não podem ser utilizados na prática, para resolver instâncias grandes da realidade, meta-heurísticas e meta-heurísticas híbridas são usadas com frequência como abordagens de resolução. Nesta pequisa, são desenvolvidas técnicas que combinam programação matemática e heurísticas, denominadas mateheurísticas, para resolver de maneira eficiente e robusta algumas variações de problemas de geração de quadros de horários escolares. Embora neste trabalho sejam abordados problemas encontrados no contexto de instituições brasileiras, os métodos propostos também podem ser aplicados em problemas similares oriundo de outros países.
The school timetabling is a classic optimization problem that has been extensively studied due to its practical and theoretical importance. It consists in scheduling a set of class-teacher meetings in a prefixed period of time, satisfying requirements of different types. Given the combinatorial nature of this problem, solving medium and large instances of timetabling to optimality is a challenging task. When resources are tight, it is often difficult to find even a feasible solution. Several techniques have been developed in the scientific literature to tackle the high school timetabling problem, however, robust solvers do not exist yet. Since the use of exact methods, such as mathematical programming techniques, is considered impracticable to solve large real world instances, metaheuristics and hybrid metaheuristics are the most used solution approaches. In this research we develop techniques that combine mathematical programming and heuristics, so-called matheuristics, to solve efficiently and in a robust way some variants of the high school timetabling problem. Although we pay special attention to problems arising in Brazilian institutions, the proposed methods can also be applied to problems from different countries.
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42

Hachimi, Hanaa. "Hybridations d'algorithmes métaheuristiques en optimisation globale et leurs applications". Phd thesis, INSA de Rouen, 2013. http://tel.archives-ouvertes.fr/tel-00905604.

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L'optimisation des structures est un processus essentiel dans la conception des systèmes mécaniques et électroniques. Cette thèse s'intéresse à la résolution des problèmes mono-objectifs et multi-objectifs des structures mécaniques et mécatroniques. En effet, les industriels ne sont pas seulement préoccupés à améliorer les performances mécaniques des pièces qu'ils conçoivent, mais ils cherchent aussi à optimiser leurs poids, leurs tailles, ainsi que leurs coûts de production. Pour résoudre ce type de problème, nous avons fait appel à des métaheuristiques robustes qui nous permettent de minimiser le coût de production de la structure mécanique et de maximiser le cycle de vie de la structure. Alors que des méthodes inappropriées de l'évolution sont plus difficiles à appliquer à des modèles mécaniques complexes en raison de temps calcul exponentiel. Il est connu que les algorithmes génétiques sont très efficaces pour les problèmes NP-difficiles, mais ils sont très lourds et trop gourmands quant au temps de calcul, d'où l'idée d'hybridation de notre algorithme génétique par l'algorithme d'optimisation par essaim de particules (PSO) qui est plus rapide par rapport à l'algorithme génétique (GA). Dans notre expérimentation, nous avons obtenu une amélioration de la fonction objectif et aussi une grande amélioration de la minimisation de temps de calcul. Cependant, notre hybridation est une idée originale, car elle est différente des travaux existants. Concernant l'avantage de l'hybridation, il s'agit généralement de trois méthodes : l'hybridation en série, l'hybridation en parallèle et l'hybridation par insertion. Nous avons opté pour l'hybridation par insertion par ce qu'elle est nouvelle et efficace. En effet, les algorithmes génétiques se composent de trois étapes principales : la sélection, le croisement et la mutation. Dans notre cas, nous remplaçons les opérateurs de mutation par l'optimisation par essaim de particules. Le but de cette hybridation est de réduire le temps de calcul ainsi que l'amélioration la solution optimale.
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43

Carneiro, Felipe Marcus. "Avaliação de métodos heurísticos para a solução do problema de programação flowshop com tempos de setup assimétricos e dependentes da sequência". Universidade de São Paulo, 2011. http://www.teses.usp.br/teses/disponiveis/18/18156/tde-25042011-114532/.

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Este trabalho é dedicado ao problema de programação em Flowshop Permutacional com tempos de preparação (setup) assimétricos e separados dos tempos de processamento e dependentes da seqüência de execução das tarefas e tem o objetivo de minimização da duração total da programação (Makespan). Através da investigação das propriedades estruturais do problema, são desenvolvidos os parâmetros XR e QR de uma programação, que indicam ociosidade das máquinas (para valores positivos) e bloqueio das tarefas (para valores negativos). Os novos parâmetros são utilizados para propor uma melhoria no cálculo eficiente de Makespan proposto por Taillard (1990). Esta melhoria é então utilizada no desenvolvimento de uma nova heurística construtiva baseada no método NEHT-RB de Ríos-Mercado e Bard (1998b) denominada CNIT, que é comparada durante a experimentação computacional com os métodos SETUP e TOTAL, de Simons (1992) com pequenas melhorias; com a proposta da utilização da propriedade UBX de Moccellin e Nagano (2007); e com o método NEHT-RB. Os métodos são então submetidos a uma busca local descendente como proposta em Ruiz e Stützle (2008) e seus desempenhos como soluções iniciais para este procedimento de busca local são avaliados. Em seguida, um método melhorativo derivado do novo método construtivo e baseado na meta-heurística IG de Ruiz e Stützle (2008) é proposto e denominado CNIT-IG. O método é comparado com a heurística IG original submetida às diferentes soluções iniciais estudadas durante a avaliação da nova heurística construtiva. As comparações são realizadas utilizando-se o banco de dados de Taillard (1990) para o flowshop permutacional adaptado para o problema de flowshop com tempos de setup assimétricos e dependentes da seqüência. Os resultados da experimentação computacional são analisados em termos da porcentagem média de sucesso, do desvio relativo médio e em relação ao tempo médio computacional e mostram a superioridade dos resultados da nova heurística construtiva CNIT e seu alto custo computacional, de complexidade mn³. Os resultados mostram ainda a superioridade da meta-heurística CNIT-IG sobre o método IG.
This work addresses the Permutation Flowshop scheduling problem with separated sequence-dependent setup times with the objective of minimizing Makespan. Through the investigation of the problem structural properties, two scheduling parameters XR e QR are developed, they indicate the machine idleness (for positive values) and task blocking (for negative values). These new parameters are used to propose an improvement in the efficient makespan calculation as stated by Taillard (1990). This improvement is then used for development of a new constructive heuristic based on Ríos-Mercado and Bard (1998b) method NEHT-RB nominated CNIT, and it is compared during computational experimentation with the methods SETUP and TOTAL of Simons (1992), with slight improvements; with the proposal of property UBX from Moccellin and Nagano (2007) and with NEHT-RB method. The methods are then submitted to descent local search as proposed in Ruiz and Stützle (2008) and its performance as initial solutions for this local search procedure is evaluated. Next, an improvement method derivate from the new constructive method and based on metaheuristic IG from Ruiz and Stützle (2008) is proposed and nominated CNIT-IG. This method is compared with original IG submitted to different initial solutions studied during constructive heuristic evaluation. Comparisons are done using Taillards instances (1990) for standard flowshop and adapted to the flowshop with sequencedependent setup times problem. The results of computation experimentation are analyzed in terms of average percentage of success, average relative percentage deviation and average computational time and show superiority of new constructive heuristic CNIT-IG and its high computational cost, with complexity mn³. The results also show superiority of metaheuristic CNIT-IG over IG method.
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SIRIGU, GIUSEPPE. "Planning and reconfigurable control of a fleet of unmanned vehicles for taxi operations in airport environment". Doctoral thesis, Politecnico di Torino, 2017. http://hdl.handle.net/11583/2675463.

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The optimization of airport operations has gained increasing interest by the aeronautical community, due to the substantial growth in the number of airport movements (landings and take-offs) experienced in the past decades all over the world. Forecasts have confirmed this trend also for the next decades. The result of the expansion of air traffic is an increasing congestion of airports, especially in taxiways and runways, leading to additional amount of fuel burnt by airplanes during taxi operations, causing additional pollution and costs for airlines. In order to reduce the impact of taxi operations, different solutions have been proposed in literature; the solution which this dissertation refers to uses autonomous electric vehicles to tow airplanes between parking lots and runways. Although several analyses have been proposed in literature, showing the feasibility and the effectiveness of this approach in reducing the environmental impact, at the beginning of the doctoral activity no solutions were proposed, on how to manage the fleet of unmanned vehicles inside the airport environment. Therefore, the research activity has focused on the development of algorithms able to provide pushback tractor (also referred as tugs) autopilots with conflict-free schedules. The main objective of the optimization algorithms is to minimize the tug energy consumption, while performing just-in-time runway operations: departing airplanes are delivered only when they can take-off and the taxi-in phase starts as soon as the aircraft clears the runway and connects to the tractor. Two models, one based on continuous time and one on discrete time evolution, were developed to simulate the taxi phases within the optimization scheme. A piecewise-linear model has also been proposed to evaluate the energy consumed by the tugs during the assigned missions. Furthermore, three optimization algorithms were developed: two hybrid versions of the particle swarm optimization and a tree search heuristic. The following functional requirements for the management algorithm were defined: the optimization model must be easily adapted to different airports with different layout (reconfigurability); the generated schedule must always be conflict-free; and the computational time required to process a time horizon of 1h must be less than 15min. In order to improve its performance, the particle swarm optimization was hybridized with a hill-climb meta-heuristic; a second hybridization was performed by means of the random variable search, an algorithm of the family of the variable neighborhood search. The neighborhood size for the random variable search was considered varying with inverse proportionality to the distance between the actual considered solution and the optimal one found so far. Finally, a tree search heuristic was developed to find the runway sequence, among all the possible sequences of take-offs and landings for a given flight schedule, which can be realized with a series of taxi trajectories that require minimum energy consumption. Given the taxi schedule generated by the aforementioned optimization algorithms a tug dispatch algorithm, assigns a vehicle to each mission. The three optimization schemes and the two mathematical models were tested on several test cases among three airports: the Turin-Caselle airport, the Milan-Malpensa airport, and the Amsterdam airport Schiphol. The cost required to perform the generated schedules using the autonomous tugs was compared to the cost required to perform the taxi using the aircraft engines. The proposed approach resulted always more convenient than the classical one.
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Gomes, Fabrício Maciel [UNESP]. "Diferentes métodos de aglutinação para melhoria de processos com múltiplas respostas". Universidade Estadual Paulista (UNESP), 2015. http://hdl.handle.net/11449/132419.

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Empresas não medem esforços para aperfeiçoar seus processos e produtos de acordo com diferentes critérios para satisfazer as exigências e necessidades dos clientes em busca de um padrão de competitividade superior ao de suas concorrentes. Neste cenário é muito comum a necessidade de se estabelecer condições que resultem na melhoria de mais de um critério de forma simultânea. Neste trabalho foi realizada uma avaliação da utilização de quatro métodos que utilizam as Meta-heurísticas Recozimento Simulado, Algoritmo Genético, Recozimento Simulado combinado com o método Nelder Mead Simplex e algoritmo genético combinado com o método Nelde-Mead simplex para o estabelecimento de melhoria das condições de processos com múltiplas respostas. Para a avaliação dos métodos propostos foram utilizados problemas-teste criteriosamente selecionados na literatura de forma a serem analisados casos com diferente número de variáveis, número de respostas e tipos de resposta. A aglutinação das respostas foi realizada por quatro métodos diferentes: Desirability, Desvio Médio Percentual, Programação por Compromisso e Programação por Compromisso normalizada pela distância euclidiana. A avaliação dos métodos foi realizada por meio de comparação entre os resultados obtidos na utilização de um mesmo método de aglutinação, determinando assim a eficiência do método de busca. Os resultados obtidos na avaliação dos métodos sugerem a aplicação do método do algoritmo genético quando se pretende estabelecer parâmetros que resultem na melhoria de processos com múltiplas respostas, em particular quando essas respostas são modeladas por equações com termos cúbicos, independentemente do número de termos que possam conter, do tipo de respostas e do número de variáveis.
Companies go to great lengths to improve its processes and products according to different criteria to meet the demands and needs of customers looking for a higher standard of competitiveness to that of their competitors. This scenario is very common the need to establish conditions that result in the improvement of more than one criterion simultaneously. This work was carried out an evaluation of the use of four methods that use Metaheuristics Simulated Annealing, Genetic Algorithms, Simulated Annealing combined with the Nelder Mead Simplex method and genetic algorithm combined with Nelde Mead simplex method for the improvement of establishing the conditions of processes with multiple answers. For the evaluation of the proposed test methods were used in the literature problems carefully selected in order to be analyzed cases with different numbers of variables, response numbers and types of responses. In this research we used the average percentage deviation function as a way to bring together the answers. The agglutination of the answers was performed by four different methods: Desirability, Average Percentage Deviation, Compromise Programming and Compromise Programming normalized by Euclidean distance. The evaluation method was performed by comparison between the results obtained in using the same bonding method, thereby determining the efficiency of the search method. The results obtained in the evaluation of the methods suggest the application of the genetic algorithm method when you want to set parameters that result in the improvement of processes with multiple answers, particularly when these responses are modeled by equations with cubic terms, regardless of the number of terms that can contain the type of responses and the number of variables.
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46

Alves, Bruna Pardim. "Busca tabu reformulada aplicada ao problema de operação de sistemas de distribuição de energia elétrica radiais /". Ilha Solteira, 2019. http://hdl.handle.net/11449/182469.

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Orientador: Ruben Augusto Romero Lazaro
Resumo: Este trabalho apresenta uma proposta baseada na meta-heurística Busca Tabu, chamada de Busca Tabu Reformulada para resolver o problema de operação ótima dos sistemas de distribuição, utilizando uma estratégia integrada de reconfiguração e alocação de bancos de capacitores fixos e chaveados para obter a topologia radial que apresente o menor custo de operação. Para encontrar a topologia radial inicial foi aplicado o algoritmo de Prim, em que foi obtida uma solução reconfigurada, e essa solução encontrada foi submetida à uma heurística para alocação de capacitores fixos e chaveados. A proposta de solução inicial é submetida ao algoritmo de Busca Tabu Reformulada que utiliza uma vizinhança que considera como solução vizinha uma topologia vizinha da topologia radial corrente e com a proposta de alocação de bancos de capacitores modificada. Como proposta da metodologia Busca Tabu Reformulada o procedimento é repetido até um critério de parada definido. Todos os programas foram escritos em linguagem FORTRAN 77. Os algoritmos propostos foram testados com os sistemas de 33, 70, 84 e 136 barras.
Abstract: This paper presents a proposal based on the Tabu Search metaheuristic called Tabu Search Reformulated to solve the problem of optimal operation of the distribution systems, using an integrated strategy of reconfiguration and allocation of fixed and switched capacitor banks to obtain the radial topology which presents the lowest operating cost. To find the initial radial topology the Prim algorithm was applied, in which a reconfigured solution was obtained, and this solution was submitted to a heuristic for the allocation of fixed and switched capacitors. The initial solution proposal is submitted to the Reformulated Tabu Search algorithm that uses a neighborhood that considers as neighbor solution a neighboring topology of the current radial topology and with the proposed allocation of modified capacitor banks. As a proposal of the Tabu Search Reformulated methodology, the procedure is repeated up to a defined stop criterion. All the programs were written in FORTRAN 77 language. The proposed algorithms were tested with the 33, 70, 84 and 136-node systems.
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47

Reis, Jorge Von Atzingen dos. "Meta-heurísticas baseadas em busca em vizinhança variável aplicadas a problemas de operação de transportes". Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/3/3138/tde-22092014-150121/.

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Esta pesquisa trata da aplicação de meta-heurísticas baseadas em busca em vizinhança variável em problemas de operação de transportes. Desta forma, buscou-se encontrar problemas complexos durante a operação de sistemas de transportes, nas grandes cidades, que possam ser resolvidos com a aplicação de meta-heurística baseada em busca em vizinhança variável. Este trabalho aborda dois diferentes problemas de planejamento e operação de transportes. O primeiro problema abordado neste trabalho é o Problema de Programação da Tabela de Horários, de Veículos e de Tripulantes de Ônibus, no qual as viagens que comporão a tabela de horários, os veículos que executarão as viagens e as tripulações que operarão os veículos são alocadas simultaneamente e de maneira integrada. O segundo problema a ser abordado é o problema de distribuição física, o qual envolve o agrupamento e a alocação de entregas a uma frota de veículos visando minimizar o frete total. Uma abordagem para a modelagem matemática deste problema é modelar como um problema de bin-packing, com bins de tamanho variável unidimensional (do inglês Variable Sized Bin-Packing Problem - VSBPP), ou seja, uma generalização do tradicional problema de bin-packing no qual bins (veículos) de diferentes capacidades e custos estão disponíveis para a alocação de um conjunto de objetos (cargas), de modo que o custo total dos bins (veículos) utilizados seja mínimo. A outra abordagem proposta para o problema de distribuição física é modelar o problema como um problema de bin-packing, com bins de tamanho variável bidimensional (do inglês Bidimensional Variable Sized Bin-Packing Problem BiD-VSBPP). Assim sendo, trata-se de uma expansão do problema de bin-packing com bins de tamanho variável unidimensional (VSBPP), no qual bins (veículos) de diferentes capacidades (capacidade volumétrica e capacidade de carga) e custos estão disponíveis para a alocação de um conjunto de objetos (cargas), os quais possuem as dimensões peso e volume, de modo que o custo total dos bins (veículos) utilizados seja mínimo. Durante a realização deste trabalho, foi desenvolvido um programa computacional em C++, o qual implementa a meta-heurística Busca em Vizinhança Variável (VNS) e duas meta-heurísticas baseadas em VNS. São apresentados resultados de experimentos computacionais com dados reais e dados benchmarking. Os resultados obtidos comprovam a eficácia das meta-heurísticas propostas.
This work approaches variable neighborhood search meta-heuristic applicate on transport operation problems. This way, we sought find complex transport operation problems in large cities that can be solved with the variable neighborhood search meta-heuristic application. This work approaches two different transport planning and operation problems. The first problem approached in this paper is the Bus Timetable Vehicle Crew Scheduling Problem, in which timetabling, bus and crew schedules are simultaneously determined in an integrated approach. The second problem to be approached is the physical distribution problem which comprises grouping and assigning deliveries to a heterogeneous fleet of vehicles aiming to minimize the total freight cost. The problem can be mathematical modeled as one-dimensional Variable Sized Bin-Packing Problem (VSBPP), a generalization of the traditional bin-packing problem, in which bins (vehicles) with different sizes and costs are available for the assignment of the objects (deliveries) such that the total cost of the used bins (vehicles) is minimized. Another proposed approach to the problem of physical distribution is model as two dimensional Variable Sized Bin-Packing Problem (BiD-VSBPP). Therefore, it is an expansion of the bin-packing problem with bins variable-length-dimensional (VSBPP), in which bins (vehicle) of different capacity (capacity and load carrying capacity) and costs are available for allocation a set of objects (loads), which have the dimensions weight and volume, so that minimized the total cost of bins (vehicle). In this work, was developed a C++ software implemented, which was implemented a meta-heuristic Variable Neighborhood Search (VNS) and two others meta-heuristics based on VNS. Computational results for real-world problems and benchmarking problems are presented, showing the effectiveness of these proposed meta-heuristics.
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48

Sanchez, Fernando Rodrigo Lopes. "Times assíncronos inicializadores para o planejamento da expansão da transmissão de energia elétrica baseados no modelo híbrido linear /". Ilha Solteira : [s.n.], 2008. http://hdl.handle.net/11449/87259.

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Orientador: Sérgio Azevedo de Oliveira
Banca: Rubén Augusto Romero Lazaro
Banca: Eduardo Nobuhiro Asada
Resumo: Neste trabalho foram implementados diversos agentes heuristicos construtivos, baseados no modelo híbrido linear, que fazem parte de um time assíncrono que tem como objetivo gerar configurações de boa qualidade para inicializar as metaheuríticas que resolvem o problema do planejamento da expansão da transmissão dos sistemas de energia elétrica. A teoria de times assíncronos foi aplicada para reunir as qualidades individuais dos métodos heurísticos, de uma maneira que, partindo de uma configuração base (sem adições) e utilizando um fluxo de dados cíclico, os agentes construtivos adicionassem circuitos a esta configuração de maneira sistemática e aleatória até que esta atenda as demandas de carga solicitadas pelo sistema elétrico em um horizonte futuro. Estas configurações foram então utilizadas por um algoritmo genético no intuito de validar a qualidade das mesmas. Os algoritmos foram implementados em Fortran, utilizando as rotinas de trocas de mensagens do LAM-MPI e simulados para sistemas teste de pequeno, médio e grande porte em ambiente de processamento distribuido. Os resultados comprovam que os times ass'ıncronos de vários metodos heurísticos são mais eficazes comparados com uma única heurística.
Abstract: In this study, it was implemented several constructive heuristic algorithms, based on hybrid linear model, which are part of a asynchronous team that aims to generate initial solutions with good quality for meta-heuristics that solve the transmission expansion planning problem of electric power systems. The theory of asynchronous team was applied to meet the individual qualities of each heuristic method, in a way that, starting from a base network configuration and using a cyclical flow of data, heuristic agents add circuits to is configuration in a systematic and random way until they meet the load demands requested by the electrical system on a future horizon. Then these configurations are utilized by a genetic algorithm in order to validate the quality of them. The algorithms were implemented in Fortran, using exchanging messages routines from LAM-MPI and simulated for small, medium and large size test-systems in distributed processing environment. The results show that the solutions obtained with asynchronous teams of several heuristic methods are more effective than the solutions with a single heuristic algorithm.
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49

Ružička, Vladimír. "Aplikace problému Obchodního cestujícího v reálném prostředí distribuční společnosti". Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2012. http://www.nusl.cz/ntk/nusl-236578.

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This paper deals with optimal distribution issues. One may find listed problems of real life linked to distribution. Moreover, there are explained travelling salesman problem, vehicle routing problem and its variants. This work brings an overview of different ways how to solve vehicle routing problem. In practical part, there is an analysis of distribution of real company. The concept of application is presented in the second part of this paper. This concept could reduce costs of distribution in analyzed company. Testing is aimed mainly on the variant VRPCL (Vehicle Routing Problem with Continuos Loading).
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Bonavero, Yoann. "Une approche basée sur les préférences et les méta-heuristiques pour améliorer l’accessibilité des pages Web pour les personnes déficientes visuelles". Thesis, Montpellier, 2015. http://www.theses.fr/2015MONTS274/document.

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Lorsque la vue, qui est un important moyen de communication, est altérée, alors l'acquisition de l'information s'en trouve modifiée, dégradée ou limitée. A l'ère du monde numérique, le Web regorge d'informations réparties sur différents sites et mises en forme par les développeurs et designers. De nombreuses pathologies visuelles peuvent entraîner des difficultés dans l'accès à ces informations. Au-delà même de ces informations, l'accès aux outils et services est lui aussi limité. Des difficultés dans la perception des couleurs, des taches dans le champ visuel ou un champ visuel réduit sont tout autant de sources de difficultés. Chaque personne a une vision qui lui est propre. Chez les personnes qui ont une basse vision, les pathologies donnent des évolutions spécifiques chez chacune d'entre elles. De plus les méthodes de compensation acquises sont différentes d'une personne à l'autre. Des outils d'assistance existent depuis de nombreuses années et tentent de répondre aux besoins des personnes ayant une basse vision en proposant des adaptations visuelles. Les principales limites de ces outils résident notamment dans le fait qu'ils ne sont pas en capacité de prendre en compte les besoins très spécifiques de chaque personne. Ces travaux de recherche se concentrent donc autour de l'analyse des besoins réels des utilisateurs et de l'élaboration d'une nouvelle approche qui se base sur les préférences personnelles de l'utilisateur. L'objectif final est d'automatiser la transformation des pages Web en fonction des préférences propres à un utilisateur pendant qu'il navigue sur le Web. Divers algorithmes ont été utilisés, notamment des algorithmes évolutionnaires, afin de réaliser des compromis entre les préférences de l'utilisateur et l'apparence originale de la page Web. La thèse développe de manière approfondie les principaux problèmes touchant les personnes en situation de basse vision et des éléments sur les modèles de couleurs et de contrastes. Puis elle présente un langage de modélisation des préférences basé sur la logique, une modélisation du problème comme un problème d'optimisation, des algorithmes de résolution, un démonstrateur, et des expérimentations sur des pages Web réelles
When the sight, which is the main communication way, is altered, then the information acquisition process is also modified, degraded or limited. In today's digital world, the Web is a wealth of information organized by designers and developers and available on different Websites. Many visual pathologies can lead to difficulties in accessing this information. Beyond this information, the access to the different tools and services is also affected. Difficulties in color perception, cloud-like white patches or dark areas in a visual field, or a reduced visual field are all sources of difficulties. Each person has a particular vision. Several persons with the same pathology may even have different visions. Several assistive tools have been proposed that apply visual adaptation, trying to meet the needs of people with low vision. Main limits of these tools are mainly the unability of taking into account the very specific needs of each person. These research works are focused on the real user's needs analysis and on making a new approach based on the personal user's preferences. The final target consists in automatizing the Web page transformation according to the specific preferences of a particular user. This transformation occurs along the navigation from page to page. Different algorithms have been used, especially evolutionary algorithms, in order to make tradeoffs between the user's preferences and the original appearance of the page. The thesis further develops main problems encountered by people with low vision and some notions on color models and contrast relations. After that, we present a preference modeling language based on logics, a modeling of the problem as an optimization problem, some resolution algorithms, a tool and experiments on several real Web pages
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