Relevant bibliographies by topics / Optimisation

Academic literature on the topic 'Optimisation'

Author: Grafiati
Published: 4 June 2021
Last updated: 3 July 2024

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Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Journal articles on the topic "Optimisation":

1

Jesudasan, Rejish, Ardeshir Hanifi, and Raffaello Mariani. "Investigating Planar and Nonplanar Wing Planform Optimisation for Ground Effect Aircraft." Aerospace 10, no. 11 (November 17, 2023): 969. http://dx.doi.org/10.3390/aerospace10110969.

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Wing-in-Ground (WIG) effect aircraft are gaining attention for their potential in reducing environmental impact. However, optimising wing planforms based solely on aerodynamics might improve performance while compromising static height stability of WIG aircraft. This study investigates the effects of planar and nonplanar wing planform optimisation for regional transport ground effect aircraft. Three distinct multiobjective wing planform optimisations are explored: planar wing optimisation, nonplanar wing optimisation, and nonplanar wingtip optimisation. These optimisations assess the impact on both aerodynamic efficiency and static height stability characteristics of a wing planform in ground effect, at three different flying altitudes. In extreme ground effect, the Pareto set includes wings with negative spanwise camber, enhancing both cushion sensation and aerodynamic efficiency by effectively utilizing ground effect, thus proving advantageous over planar wing configurations.
2

Wu, Qing, Colin Cole, Maksym Spiryagin, and Tim McSweeney. "Parallel multiobjective optimisations of draft gear designs." Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit 232, no. 3 (January 31, 2017): 744–58. http://dx.doi.org/10.1177/0954409717690981.

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This paper presents the methodology and results of the parallel multiobjective optimisations of draft gear designs. The methodology used white-box draft gear models, whose parameters were used as the optimisation variables. Two optimisation algorithms were used: genetic algorithm and particle swarm optimisation. All the optimised draft gear designs were constrained by impact tests to ensure that the optimised designs also comply with the current acceptance standards for draft gears. The performance of draft gears was assessed using whole-trip longitudinal train dynamics simulations and coupler fatigue damage calculations. Each simulation covered a round trip (loaded one way, empty on return) over a total of 640 km of track, which involved about 10 h of operational time. Three optimisation objectives were considered: minimal fatigue damage for wagon connection systems of loaded trains, minimal in-train forces for loaded trains, and minimal longitudinal wagon accelerations for empty trains. Two case studies were presented, which optimised two types of draft gears (single-stage and double-stage draft gears) using genetic algorithm and particle swarm optimisation, respectively.
3

Vankan, W. J., R. Maas, and S. Grihon. "Efficient optimisation of large aircraft fuselage structures." Aeronautical Journal 118, no. 1199 (January 2014): 31–52. http://dx.doi.org/10.1017/s0001924000008915.

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Abstract This paper presents an innovative optimisation method for aircraft fuselage structural design. Detailed local finite element analyses of panel buckling are further processed such that they can be applied as failure constraints in the global level optimisation. The high computational costs involved with the finite element analyses are limited by advanced use of surrogate modelling methods. This yields high flexibility and efficiency in the local level optimisation procedure and allows for efficient gradient based search methods as well as more costly direct search optimisations like genetic algorithms (GAs). The method is demonstrated on a composite fuselage barrel design case considering common structural sizing variables like thicknesses and stringer dimensions. Optimised barrel designs are obtained where the constraints that are derived from the panel buckling analyses are active. The total computational cost for the complete local and global level optimisation procedures is in the order of days on common-performance hardware.
4

Podobedov, Vitaly E. "DETERMINISTIC CHAOS PRODUCED BY LOCAL OPTIMISATION ALGORITHMS." Technological and Economic Development of Economy 13, no. 1 (March 31, 2007): 61–66. http://dx.doi.org/10.3846/13928619.2007.9637777.

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Deterministic chaos situations produced by local optimisation algorithms are considered. A family of test multi‐extremal functions is proposed that allows getting the collections of functions with an arbitrary pre‐defined number of the local optima. Special software is developed for generating test functions from the family, performing multiple local optimisations of different initial points, visualising the chaotic attraction regions. Properties of the regions of attraction are presented. Regularity of the attraction regions is required to be a special characteristic of the local optimisation algorithms.
5

Tomašić, Dubravko, Dragan Peraković, and Marinko Jurčević. "Interdependence between Inventory Management and Employees’ Satisfaction." PROMET - Traffic&Transportation 25, no. 3 (June 19, 2013): 245–54. http://dx.doi.org/10.7307/ptt.v25i3.909.

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The study determines the correlation between the application of advanced models and methods of inventory optimisation in the supply chain in relation to the satisfaction of employees who are responsible for managing the inventory optimisation processes. The previous studies confirm that the optimisation of inventory management in the supply chain insures competitive advantages on the market. There is space for further research of impact of the achieved inventory optimisation in the supply chain on the change of the employees’ satisfaction. The paper establishes the interrelation of the interdependence of the achieved inventory optimisations on the satisfaction of the employees and the related synergy effects of acquiring added value of the companies on the market oriented to the satisfaction of the buyers and service users. The research has defined new knowledge in interdependence of inventory management optimisation on the change of indicators of employees’ satisfaction. Based on the performed research an assumption has been created for the design of an application package (so-called XaaS-based services) for the management of interaction processes of inventory optimization in the supply chain, satisfaction of service users and employees.
6

Yudianto, Aan. "Application of Multi-objective Adjoint-based Aerodynamic Optimisation on Generic Road Vehicle with Rear Spoiler." Automotive Experiences 7, no. 1 (April 27, 2024): 28–47. http://dx.doi.org/10.31603/ae.10577.

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Finding possible solutions where there are multiple conflicting objectives to be simultaneously satisfied is a challenging situation. Multi-objective optimisation of a rear spoiler on a generic road vehicle model is carried out by using adjoint-based optimisation coupled with Computational Fluid Dynamics. The study aims to reduce the vehicle drag and increase vehicle downforce simultaneously by optimising the shape of the spoiler, by allowing the deformation to achieve the most optimised shape assuming no manufacturing constraint. The OpenFOAM software was used for the solver. A strategy for multi-objective optimisation was proposed by assigning appropriate objective function weight, leading to some possible solutions and Pareto front of the proposed design family. Five optimisation solutions of the non-dominated solution Pareto front resulting from the spoiler shape optimisation are presented, explaining the trade-off between conflicting drag and downforce objectives on the vehicle model. The baseline geometry of the simulation is in good agreement with the experimental measurement. The analysis of the shape changes in the proposed optimisation is deeply investigated in terms of the optimised geometry deformation, velocity contour comparison, recirculating region on the base, pressure coefficient comparison and stream-wise velocity component at the slant region of the model. The adjoint-based optimisation method in the presence study can handle multiple objective optimisations and generate possible optimised spoiler shapes to reduce drag and increase downforce. Free deformation of the shape yields in the unique shapes of the spoiler, enabling to manipulate of the base flow at the rear of the vehicle model.
7

Jimenez-Garcia, A., M. Biava, G. N. Barakos, K. D. Baverstock, S. Gates, and P. Mullen. "Tiltrotor CFD Part II - aerodynamic optimisation of tiltrotor blades." Aeronautical Journal 121, no. 1239 (May 2017): 611–36. http://dx.doi.org/10.1017/aer.2017.21.

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ABSTRACTThis paper presents aerodynamic optimisation of tiltrotor blades with high-fidelity computational fluid dynamics. The employed optimisation framework is based on a quasi-Newton method, and the required high-fidelity flow gradients were computed using a discrete adjoint solver. Single-point optimisations were first performed to highlight the contrasting requirements of the helicopter and aeroplane flight regimes. It is then shown how a trade-off blade design can be obtained using a multi-point optimisation strategy. The parametrisation of the blade shape allowed the twist and chord distributions to be modified and a swept tip to be introduced. The work shows how these main blade shape parameters influence the optimal performance of the tiltrotor in helicopter and aeroplane modes, and how an optimised blade shape can increase the overall tiltrotor performance. Moreover, in all the presented cases, the accuracy of the adjoint gradients resulted in a small number of flow evaluations for finding the optimal solution, thus indicating gradient-based optimisation as a viable tool for modern tiltrotor design.
8

Paler, Alexandru, and Robert Basmadjian. "Energy Cost of Quantum Circuit Optimisation: Predicting That Optimising Shor’s Algorithm Circuit Uses 1 GWh." ACM Transactions on Quantum Computing 3, no. 1 (March 31, 2022): 1–14. http://dx.doi.org/10.1145/3490172.

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Quantum circuits are difficult to simulate, and their automated optimisation is complex as well. Significant optimisations have been achieved manually (pen and paper) and not by software. This is the first in-depth study on the cost of compiling and optimising large-scale quantum circuits with state-of-the-art quantum software. We propose a hierarchy of cost metrics covering the quantum software stack and use energy as the long-term cost of operating hardware. We are going to quantify optimisation costs by estimating the energy consumed by a CPU doing the quantum circuit optimisation. We use QUANTIFY, a tool based on Google Cirq, to optimise bucket brigade QRAM and multiplication circuits having between 32 and 8,192 qubits. Although our classical optimisation methods have polynomial complexity, we observe that their energy cost grows extremely fast with the number of qubits. We profile the methods and software and provide evidence that there are high constant costs associated to the operations performed during optimisation. The costs are the result of dynamically typed programming languages and the generic data structures used in the background. We conclude that state-of-the-art quantum software frameworks have to massively improve their scalability to be practical for large circuits.
9

Cvetkovski, Goga, and Lidija Petkovska. "Design Improvement of Permanent Magnet Motor Using Single- and Multi-Objective Approaches." Power Electronics and Drives 9, no. 1 (January 1, 2024): 34–49. http://dx.doi.org/10.2478/pead-2024-0003.

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Abstract Optimisation, or optimal design, has become a fundamental aspect of engineering across various domains, including power devices, power systems, and industrial systems. Engineers and academics have been actively involved in optimising these systems to achieve better performance, efficiency, and cost-effectiveness. Optimising electrical machines, including permanent magnet motors, is a complex task. It often involves solving intricate problems with various parameters and constraints. Engineers use different optimisation methods to tackle these challenges. Depending on the specific requirements and goals of a design project, engineers may employ either single-objective or multi-objective optimisation approaches. Single-objective optimisation focuses on optimising a single objective, while multi-objective optimisation considers multiple conflicting objectives. In optimisation, objective functions are mathematical representations of what needs to be optimised. In this case, optimising the efficiency of the motor, reducing cogging torque, and minimising the total weight of active materials are defined as possible objective functions. Genetic algorithms are nature based algorithms that are commonly used in engineering to find optimal solutions to complex problems, including those with multiple objectives. In this paper, after conducting optimisations using different objective functions and methods, a comparative analysis of the results is performed. This helps in understanding the trade-offs and benefits of different design choices. Finite element analysis (FEA) is a computational method used to analyse the physical properties and behaviours of complex structures and systems. In this case, FEA is used to validate and analyse selected optimisation solutions to ensure they meet the desired characteristics and parameters. Overall, this work demonstrates the interdisciplinary nature of engineering, where mathematics, computer science (for optimisation algorithms), and physics (for FEA) converge to improve the performance and efficiency of electrical machines. It also underscores the importance of considering multiple objectives in design processes to find optimal solutions that strike a balance between competing goals.
10

Liew, Jaime, Riccardo Riva, Mikkel Friis-Møller, and Tuhfe Göçmen. "Wind Farm Control Optimisation Under Load Constraints Via Surrogate Modelling." Journal of Physics: Conference Series 2767, no. 9 (June 1, 2024): 092039. http://dx.doi.org/10.1088/1742-6596/2767/9/092039.

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Abstract In the field of wind farm control, wake steering has shown the potential to increase the power output of a wind farm by deflecting wakes away from downstream turbines. However, in some wake steering scenarios, the fatigue damage experienced by the turbines can increase, particularly when the wakes partially overlap a downstream rotor. It is for this reason that fatigue load constraints should be introduced into the control optimisation process. Unfortunately, wind turbine loads are notoriously difficult to predict, requiring expensive aeroelastic simulations. In this study, we present a wind farm control optimisation with load constraints using surrogate models to estimate the fatigue damage of each turbine in a wind farm designed for maximum energy production. We use the state-of-the-art aeroelastic wind farm simulator, HAWC2Farm, to produce a comprehensive data set of fatigue loads, which is then used to train surrogate models for rapid execution during an optimisation loop. The inputs of the surrogate model are chosen using the most significant modes from a proper orthogonal decomposition. Artificial neural networks are used for the surrogate models, and the wind farm control optimisation is carried out using OpenMDAO. Finally, a wind farm control optimisation with load constraints using wake steering is performed. The presented methodology for surrogate modelling and control optimisation is significant to produce accurate set point optimisations for wind farms while recognising the implications to turbine fatigue loads.
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Journal articles Dissertations / Theses Books

Dissertations / Theses on the topic "Optimisation":

1

Moser, Irene. "Applying external optimisation to dynamic optimisation problems." Swinburne Research Bank, 2008. http://hdl.handle.net/1959.3/22526.

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Thesis (Ph.D) - Swinburne University of Technology, Faculty of Information & Communication Technologies, 2008.
[A thesis submitted in total fulfillment of the requirements of for the degree of Doctor of Philosophy, Faculty of Information and Communication Technologies, Swinburne University of Technology, 2008]. Typescript. Includes bibliographical references p. 193-201.
2

Poole, Daniel. "Efficient optimisation methods for generic aerodynamic shape optimisation." Thesis, University of Bristol, 2017. http://hdl.handle.net/1983/66904840-aed2-4797-9fb1-9d2b1d8b86ae.

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Aerodynamic shape optimisation amalgamates three, often independent, modules; a shape control system, a flow solver and an optimisation algorithm. The cornerstone is the shape control system, which governs the mapping between the real, continuous aerodynamic shape to the discretised surface that is used within the computational domain, using a set of design variables. The overall objectives of this work are to have efficient optimisation and design space exploration. Hence the focus of this work is first, shape control, and second, the optimisation algorithm. First, a novel shape control system has been developed and is presented in this thesis that gives large design space coverage using very few design variables. The method uses a singular value decomposition (SVD) approach to extract the optimal reduced set of orthogonal aerofoil shape 'modes' from an existing library of aerofoils. Performing an SVD is guaranteed to produce an optimal representation of the original library; a powerful result. It is shown that different initial libraries of aerofoils result in different modes, each suited to their own design specification i.e. modes from transonic aerofoils are effective for transonic design. This method is shown to be highly efficient, with very few shape modes (fewer than ten, and sometimes as few as six) required to represent a wide range of aerofoils to within a typical wind tunnel tolerance. This is compared to the PARSEC method, which fails to represent any of the aerofoils tested to within the required tolerance, and the Hick-Henne method, that requires 12 to 16 bumps. The efficiency that comes with the aerofoil modes can be fully exploited by performing global optimisation, and this is the second objective of this work. However, aerodynamic optimisation requires satisfaction of constraints. Constraint handling occurs using ad hoc techniques that are often not universally transferable between global optimisation algorithms. As such, an effective universal constraint handling framework has been developed and presented in this thesis. To demonstrate the universality of the framework, it is coupled to four different global optimisation algorithms (particle swarm, gravitational search, a hybrid of the two, and differential evolution) and used to optimise a number of analytical benchmark problems. It is compared, and shown to outperform, other universal constraint handling techniques that use penalty and feasible direction approaches, with feasibility rates shown to be higher than 90% with the new framework, compared to 50-80% for the other frameworks. When coupling differential evolution to the new framework, on a number of benchmark engineering problems, the results are equivalent to the best results published in the literature. The development of efficient shape design variables and an effective constraint handling framework allows efficient global aerodynamic optimisation to be realised. A large number of transonic inviscid and viscous aerofoil optimisations are presented and it is demonstrated that as few as six aerofoil modes are sufficient to produce shock-free solutions for inviscid and viscous cases. Global wing planform optimisations are also considered. It is shown that when using chord variations only, two distinct minima are found that have almost equivalent drag reductions (around 25%) but at completely different locations within in the design space. The addition of further planform and non-planar design variables increases the multimodality found in the design space.
3

Tall, Abdoulaye. "Optimisation et Auto-Optimisation dans les réseaux LTE." Thesis, Avignon, 2015. http://www.theses.fr/2015AVIG0208/document.

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Le réseau mobile d’Orange France comprend plus de 100 000 antennes 2G, 3G et 4G sur plusieurs bandes de fréquences sans compter les nombreuses femto-cells fournies aux clients pour résoudre les problèmes de couverture. Ces chiffres ne feront que s’accroître pour répondre à la demande sans cesse croissante des clients pour les données mobiles. Cela illustre le défi énorme que rencontrent les opérateurs de téléphonie mobile en général à savoir gérer un réseau aussi complexe tout en limitant les coûts d’opération pour rester compétitifs. Cette thèse s’attache à utiliser le concept SON (réseaux auto-organisants) pour réduire cette complexité en automatisant les tâches répétitives ou complexes. Plus spécifiquement, nous proposons des algorithmes d’optimisation automatique pour des scénarios liés à la densification par les small cells ou les antennes actives. Nous abordons les problèmes classiques d’équilibrage de charge mais avec un lien backhaul à capacité limitée et de coordination d’interférence que ce soit dans le domaine temporel (notamment avec le eICIC) ou le domaine fréquentiel. Nous proposons aussi des algorithmes d’activation optimale de certaines fonctionnalités lorsque cette activation n’est pas toujours bénéfique. Pour la formulation mathématique et la résolution de tous ces algorithmes, nous nous appuyons sur les résultats de l’approximation stochastique et de l’optimisation convexe. Nous proposons aussi une méthodologie systématique pour la coordination de multiples fonctionnalités SON qui seraient exécutées en parallèle. Cette méthodologie est basée sur les jeux concaves et l’optimisation convexe avec comme contraintes des inégalités matricielles linéaires
The mobile network of Orange in France comprises more than 100 000 2G, 3G and 4G antennas with severalfrequency bands, not to mention many femto-cells for deep-indoor coverage. These numbers will continue toincrease in order to address the customers’ exponentially increasing need for mobile data. This is an illustrationof the challenge faced by the mobile operators for operating such a complex network with low OperationalExpenditures (OPEX) in order to stay competitive. This thesis is about leveraging the Self-Organizing Network(SON) concept to reduce this complexity by automating repetitive or complex tasks. We specifically proposeautomatic optimization algorithms for scenarios related to network densification using either small cells orActive Antenna Systems (AASs) used for Vertical Sectorization (VeSn), Virtual Sectorization (ViSn) and multilevelbeamforming. Problems such as load balancing with limited-capacity backhaul and interference coordination eitherin time-domain (eICIC) or in frequency-domain are tackled. We also propose optimal activation algorithms forVeSn and ViSn when their activation is not always beneficial. We make use of results from stochastic approximationand convex optimization for the mathematical formulation of the problems and their solutions. We also proposea generic methodology for the coordination of multiple SON algorithms running in parallel using results fromconcave game theory and Linear Matrix Inequality (LMI)-constrained optimization
4

Salazar, Lechuga Maximino. "Multi-objective optimisation using sharing in swarm optimisation algorithms." Thesis, University of Birmingham, 2009. http://etheses.bham.ac.uk//id/eprint/303/.

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Many problems in the real world are multi-objective by nature, this means that many times there is the need to satisfy a problem with more than one goal in mind. These type of problems have been studied by economists, mathematicians, between many more, and recently computer scientists. Computer scientists have been developing novel methods to solve this type of problems with the help of evolutionary computation. Particle Swarm Optimisation (PSO) is a relatively new heuristic that shares some similarities with evolutionary computation techniques, and that recently has been successfully modified to solve multi-objective optimisation problems. In this thesis we first review some of the most relevant work done in the area of PSO and multi-objective optimisation, and then we proceed to develop an heuristic capable to solve this type of problems. An heuristic, which probes to be very competitive when tested over synthetic benchmark functions taken from the specialised literature, and compared against state-of-the-art techniques developed up to this day; we then further extended this heuristic to make it more competitive. Almost at the end of this work we incursion into the area of dynamic multi-objective optimisation, by testing the capabilities and analysing the behaviour of our technique in dynamic environments.
5

Yin, Xuefei. "Application of multidisciplinary design optimisation to engine calibration optimisation." Thesis, University of Bradford, 2012. http://hdl.handle.net/10454/5630.

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Automotive engines are becoming increasingly technically complex and associated legal emissions standards more restrictive, making the task of identifying optimum actuator settings to use significantly more difficult. Given these challenges, this research aims to develop a process for engine calibration optimisation by exploiting advanced mathematical methods. Validation of this work is based upon a case study describing a steady-state Diesel engine calibration problem. The calibration optimisation problem seeks an optimal combination of actuator settings that minimises fuel consumption, while simultaneously meeting or exceeding the legal emissions constraints over a specified drive cycle. As another engineering target, the engine control maps are required as smooth as possible. The Multidisciplinary Design Optimisation (MDO) Frameworks have been studied to develop the optimisation process for the steady state Diesel engine calibration optimisation problem. Two MDO strategies are proposed for formulating and addressing this optimisation problem, which are All At Once (AAO), Collaborative Optimisation. An innovative MDO formulation has been developed based on the Collaborative Optimisation application for Diesel engine calibration. Form the MDO implementations, the fuel consumption have been significantly improved, while keep the emission at same level compare with the bench mark solution provided by sponsoring company. More importantly, this research has shown the ability of MDO methodologies that manage and organize the Diesel engine calibration optimisation problem more effectively.
6

Heinonen, Annika. "Process Optimisation - An empirical study of process optimisation in Finland." Thesis, Högskolan i Jönköping, Internationella Handelshögskolan, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-17746.

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The objective of this master’s thesis is to determine methods for improving a company’s business processes without investing in new technology and whether a relatively small company can benefit from investing in technology. This study determines the meaning of process optimisation and how it should be conducted. Using existing theory and the case of a logistics company operating in Finland, this research attempts to identify hindrances and find opportunities for the company to develop their processes through process optimisation without technology. Different public bodies in Finland (such as the Finnish government and Statistics Finland) have stated that Finnish logistics requires development and have recommended new technology as a solution to the issue. However, the lack of information on the Finnish logistics business sector makes such statements by public bodies difficult to analyse. Process optimisation has been revealed to be more complex than expected. Many theories available today examine and recommend different technological solutions to execute companies’ work processes. However, a theory is needed on how process optimisation can be carried out at a company lacking technology. Process optimisation consists of process modelling and process analysis. Process modelling appears to be the most significant and crucial aspect of process optimisation. Order-to-delivery processes cannot be optimised within a company if the company does not understand the entirety of such processes. Knowledge of the process has been highlighted as being key to understanding a company’s processes at a high level. The case company in this study showed that process optimisation is possible without implementing new technology; instead, optimisation required additional human capital and a stronger focus on a company’s internal business processes. Technology-based solutions for process optimisation are tempting to implement as doing so may be believed to save time, but no automated solution is able to reveal a company’s critical information if the company does not know what it is looking for and cannot identify its problem areas. This research includes a single case study. The results indicate that whether a relatively small company could benefit from investing in technology is unclear, and the lack of research on process optimisation at Finnish companies resulted in limited findings and analysis. Several different scientific articles presented technology implementation successes and failures, but did not reveal information on the steps taken by the companies.
7

Soltun, Sindre. "Fleet Management Optimisation." Thesis, Norwegian University of Science and Technology, Department of Telematics, 2007. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-10147.

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This Master's Thesis is built around the concept of fleet management, focusing on designing and implementing a solution for such a purpose. As a target domain for this proposed system snow clearing has been chosen, and it is presented as background for the system realisation. An important feature in a fleet management system is route optimisation. Estimations based on real-world data can be used to construct more effective routes. This optimisation process is not straightforward though, as it belongs in a domain called Vehicle Routing Problems. These problems effectively becomes unsolvable for realisticly sized datasets using traditional optimisation methods, and the reasons behind this and alternative solution approaches are presented in this text. Enhanced fleet monitoring is another target for a fleet management system, and this requires modern localisation technology. To continuously be aware of every unit's position, an accurate tracking mechanism is necessary. Such mechanisms are also presented, focusing mainly on the Global Positioning System (GPS). To create the actual solution, a thorough design phase was necessary. The results of this process, including a requirement specification, a design model and a test plan, are included in this report. Based on the design phase parts of the system have been implemented, such as the graphical user interfaces and communication. The main focus of the implemetation has been on the optimisation process though, and several approaches have been tested. All implentation results, including testing results based on the test plan, can be found in this report. To offer operators a clear view of the positions of the fleet's units, a part of the system will need to work as a geographical information system. This functionality has not been implemented, but its requirements are discussed as well. To add a market perspective to this thesis a business model for a company developing the proposed solution is presented, along with a view on how the solution may affect the business model of companies that implement it into their operations. The last part of the report presents a discussion around the proposed solution. This discussion focuses on the qualities and shortcomings of the solution, how it compares to already existing solutions in the market, and what future work is necessary for the system to be completed.

8

Tournois, Jane. "Optimisation de maillages." Phd thesis, Université de Nice Sophia-Antipolis, 2009. http://tel.archives-ouvertes.fr/tel-00451619.

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Dans cette thèse, une approche pratique pour la génération de maillages triangulaires isotropes est proposée. En 2D comme en 3D, l'ob jectif consiste à mailler un domaine donné, pouvant avoir une géométrie complexe. L'approche présentée consiste à entrelacer des étapes de raffinement de Delaunay et des étapes d'optimisation de maillages dans le but de générer des maillages gradés de qualité. L'utilisateur peut contrôler les caractéristiques du maillage en définissant des critères de taille et de forme des simplexes, ainsi que de topologie et d'approximation. Les méthodes par éléments finis, largement utilisées en simulation, nécessitent des maillages gradés, composés de simplexes bien formés. Des alternatives aux méthodes de raffinement de Delaunay usuelles sont développées. Les méthodes d'optimisation de maillages proposées permettent d'optimiser la position des sommets intérieurs et de ceux du bord. Les caractéristiques du bord du domaine à mailler, et en particulier des arêtes vives, sont préservées par ces méthodes. En 2D, l'optimisation est basée sur l'algorithme de Lloyd et les diagrammes de Voronoi centrés (CVT). En 3D, une extension naturelle des triangulations de Delaunay optimales (ODT) de Chen, capable d'optimiser la position des sommets du bord du maillage, est introduite. Notre algorithme de maillage tétraédrique est enrichi par une étape de post-traitement permettant d'améliorer de façon significative la qualité des angles dièdres du maillage. Nous montrons que l'entrelacement d'étapes de raffinement et d'optimisation permet d'obtenir des maillages de meilleure qualité que ceux générés par les méthodes connues en termes d'angles dans les simplexes et de complexité.
9

Ning, Michael Zhu. "Relational combinatorial optimisation." Thesis, University of Oxford, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.284507.

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Oliver, Kathryn E. "UMTS network optimisation." Thesis, Cardiff University, 2005. http://orca.cf.ac.uk/54561/.

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Network operators desire effective, pragmatic solutions to instances of the cell planning problem in order to improve their quality of service, enhance network coverage and capacity capability, and ultimately increase company profits. Previ ous cell plans have been constructed manually but these methods do not produce the best network configuration. More reliance has since been placed on automated cell planning to produce effective solutions. The introduction of the Universal Mobile Telecommunication System (UMTS) emphasizes the need for high perfor mance planning tools. Motivated by a discussion of the literature concerning cell planning, an existing model for Global System for Mobile Communication (GSM) is modified to take account of the requirements of UMTS networks. A suite of test cases is created using a purpose-built problem generator, including problems with a range of site and traffic distributions for rural, suburban and urban markets. Traditionally, cell planning has been seen purely as an optimisation problem, neglecting the pre-optimisation stage of network dimensioning. This thesis inves tigates the effect of network dimensioning as a precursor to optimisation demon strating the benefits of cell planning in three stages consisting of site estimation, site selection and optimisation. The first stage, site estimation, utilises previously published lower bounding techniques to provide a means of approximating the number of sites required to meet capacity targets in the uplink and downlink. Site selection compares random selection to three newly developed algorithms to make effective automatic selections of sites from a candidate set. The final optimiza tion phase presents a framework based on the tabu search meta-heuristic capable of optimising the dimensioned network designs with respect to the representative operational scenarios. Multiple traffic snapshot evaluations are considered in the optimisation objective function.
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Books on the topic "Optimisation":

1

Korte, Bernhard, Jens Vygen, Jean Fonlupt, and Alexandre Skoda. Optimisation combinatoire. Paris: Springer Paris, 2010. http://dx.doi.org/10.1007/978-2-287-99037-3.

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Hiriart-Urruty, Jean-Baptiste. L' optimisation. Paris: Presses universitaires de France, 1996.

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Pham, D. T., and D. Karaboga. Intelligent Optimisation Techniques. London: Springer London, 2000. http://dx.doi.org/10.1007/978-1-4471-0721-7.

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Dolgui, Alexandre, Jerzy Soldek, and Oleg Zaikin, eds. Supply Chain Optimisation. Boston, MA: Springer US, 2005. http://dx.doi.org/10.1007/b101812.

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Brabazon, Anthony, and Seán McGarraghy. Foraging-Inspired Optimisation Algorithms. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-59156-8.

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Šibalija, Tatjana V., and Vidosav D. Majstorović. Advanced Multiresponse Process Optimisation. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-19255-0.

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Gandibleux, Xavier, Marc Sevaux, Kenneth Sörensen, and Vincent T’kindt, eds. Metaheuristics for Multiobjective Optimisation. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-17144-4.

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Lewis, Andrew, Sanaz Mostaghim, and Marcus Randall, eds. Biologically-Inspired Optimisation Methods. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01262-4.

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G, Hunt D., Collins M. W, and Atherton M. A. 1942-, eds. Optimisation mechanics in nature. Southampton, UK: WIT, 2004.

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Lin, Grier C. I. CIM justification and optimisation. London: Taylor & Francis, 2000.

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Book chapters on the topic "Optimisation":

1

Zemella, Giovanni, and Andrea Faraguna. "Optimisation." In Evolutionary Optimisation of Façade Design, 33–63. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-5652-9_2.

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Watson, Des. "Optimisation." In Undergraduate Topics in Computer Science, 177–203. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52789-5_7.

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Woodford, C., and C. Phillips. "Optimisation." In Numerical Methods with Worked Examples: Matlab Edition, 169–95. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-1366-6_8.

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Soldani, David, Giovanni Giambiasi, Kimmo Valkealahti, Mikko Kylväjä, Massimo Barazzetta, Mariagrazia Squeo, Jaroslav Uher, Luca Allegri, and Jaana Laiho. "Optimisation." In QoS and QoE Management in UMTS Cellular Systems, 385–439. Chichester, UK: John Wiley & Sons, Ltd, 2006. http://dx.doi.org/10.1002/9780470034057.ch10.

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French, Michael J. "Optimisation." In Conceptual Design for Engineers, 55–84. London: Springer London, 1999. http://dx.doi.org/10.1007/978-1-4471-3627-9_3.

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Antia, H. M. "Optimisation." In Numerical Methods for Scientists and Engineers, 345–400. Gurgaon: Hindustan Book Agency, 2012. http://dx.doi.org/10.1007/978-93-86279-52-1_8.

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Kangas, Annika, Mikko Kurttila, Teppo Hujala, Kyle Eyvindson, and Jyrki Kangas. "Optimisation." In Decision Support for Forest Management, 127–66. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23522-6_6.

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Croall, Ian F., and John P. Mason. "Optimisation." In Industrial Applications of Neural Networks, 161–218. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-84837-7_6.

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Dyke, Phil. "Optimisation." In Advanced Calculus, 49–61. London: Macmillan Education UK, 1998. http://dx.doi.org/10.1007/978-1-349-14076-3_4.

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Osterhage, Wolfgang W. "Optimisation." In Computer Performance Optimization, 67–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-29971-1_5.

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Conference papers on the topic "Optimisation":

1

Maumela, Tshifhiwa, Fulufhelo Nelwamondo, and Tshilidzi Marwala. "Portfolio Optimisation Using Ulimisana Optimisation Algorithm." In 2022 8th International Conference on Control, Decision and Information Technologies (CoDIT). IEEE, 2022. http://dx.doi.org/10.1109/codit55151.2022.9803923.

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John, Alistair, Guglielmo Vivarelli, Ning Qin, and Shahrokh Shahpar. "Using Feature-Based Mesh Adaptation to Improve the Adjoint Optimisation of Transonic Compressor Blades." In ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/gt2020-15351.

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Abstract The benefit of mesh adaptation to improve the optimisation process of turbomachinery components is here demonstrated for the first time. Mesh movement is used to automatically cluster and align the cells with significant flow features such as shocks, shock-induced separation and wakes for every geometry tested during a transonic compressor blade optimisation. Using mesh movement means that the same size grid is used while significantly improving the accuracy of the simulation and resulting adjoint gradients. A method is demonstrated to automatically carry out feature based mesh movement during every step of an adjoint optimisation process. Optimisations are carried out using the adaptation method and also using the starting mesh as a comparison. It is shown that (when tested on a very fine grid) the adaptation-optimisation process results in a better design, due to more accurate flow and gradient prediction throughout the optimisation process. A cost breakdown of the process is given to show that using adaptation during the optimisation process only increases the overall optimisation cost by a small amount, but results in greater efficiency of the final blade design.
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Cirmirakis, D., and J. K. Pollard. "Rowing optimisation." In 2009 IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS). IEEE, 2009. http://dx.doi.org/10.1109/idaacs.2009.5343005.

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Branke, Juergen. "Simulation optimisation." In GECCO '19: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3319619.3323385.

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Branke, Juergen. "Simulation optimisation." In GECCO '18: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3205651.3207887.

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Branke, Juergen. "Simulation Optimisation." In GECCO '16: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2908961.2926995.

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Assimi, Hirad, Frank Neumann, Markus Wagner, and Xiaodong Li. "Novelty particle swarm optimisation for truss optimisation problems." In GECCO '21: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3449726.3459572.

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Vikhe, Akshay Sunil, and A. A. Kalage. "Power System Optimisation using Ant Lion Optimisation Technique." In 2019 3rd International conference on Electronics, Communication and Aerospace Technology (ICECA). IEEE, 2019. http://dx.doi.org/10.1109/iceca.2019.8822093.

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Rezaee Jordehi, Ahmad, Jasronita Jasni, Noor Izzri Abdul Wahab, and Mohd Zainal Abidin Abd Kadir. "Particle swarm optimisation applications in FACTS optimisation problem." In 2013 IEEE 7th International Power Engineering and Optimization Conference (PEOCO). IEEE, 2013. http://dx.doi.org/10.1109/peoco.2013.6564541.

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Pauley, Michael, and Jonathan H. Manton. "Optimisation geometry and its implications for optimisation algorithms." In 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP). IEEE, 2017. http://dx.doi.org/10.1109/camsap.2017.8313169.

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Reports on the topic "Optimisation":

1

Horrocks, Ian, and Stephan Tobies. Optimisation of Terminological Reasoning. Aachen University of Technology, 1999. http://dx.doi.org/10.25368/2022.99.

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An extended abstract of this report was submitted to the Seventh International Conference on Principles of Knowledge Representation and Reasoning (KR2000). When reasoning in description, modal or temporal logics it is often useful to consider axioms representing universal truths in the domain of discourse. Reasoning with respect to an arbitrary set of axioms is hard, even for relatively inexpressive logics, and it is essential to deal with such axioms in an efficient manner if implemented systems are to be effective in real applications. This is particularly relevant to Description Logics, where subsumption reasoning with respect to a terminology is a fundamental problem. Two optimisation techniques that have proved to be particularly effective in dealing with terminologies are lazy unfolding and absorption. In this paper we seek to improve our theoretical understanding of these important techniques. We define a formal framework that allows the techniques to be precisely described, establish conditions under which they can be safely applied, and prove that, provided these conditions are respected, subsumption testing algorithms will still function correctly. These results are used to show that the procedures used in the FaCT system are correct and, moreover, to show how effiency an be significantly improved, while still retaining the guarantee of correctness, by relaxing the safety conditions for absorption.
2

Job, P. K., R. Blair, and L. Price. Optimisation studies for scintillator plate calorimeter. Office of Scientific and Technical Information (OSTI), December 1990. http://dx.doi.org/10.2172/10184695.

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Kepser, Stephan, and Jörn Richts. Optimisation Techniques for Combining Constraint Solvers. Aachen University of Technology, 1996. http://dx.doi.org/10.25368/2022.72.

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Thompson. L52208 Coating and Backfill System Optimisation. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), May 2004. http://dx.doi.org/10.55274/r0010964.

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This project focuses specifically on the mechanical properties of a pipeline coating in relation to the need to use imported or site-processed bedding and padding materials to create the pipelines habitat. This project assesses whether mainline and field joint coatings, typically utilized for pipeline protection, possessed sufficient mechanical resistance to withstand backfilling, commissioning and service with bedding and padding materials that had undergone minimal processing. The project was carried out in two phases, the first involved a series of large-scale tests to assess the impact, penetration and abrasion resistance of three mainline and two field joint coatings. The second phase involved a series of small-scale laboratory tests to assess the same three mechanical properties. Includes a spreadhseet to help cost optimize backfilling pipelines.
5

Dixon, L. C., and R. C. Price. Optimisation Algorithms for Highly Parallel Computer Architectures. Fort Belvoir, VA: Defense Technical Information Center, December 1990. http://dx.doi.org/10.21236/ada235911.

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6

Nobile, F., Q. Ayoul-Guilmard, S. Ganesh, M. Nuñez, A. Kodakkal, C. Soriano, and R. Rossi. D6.5 Report on stochastic optimisation for wind engineering. Scipedia, 2022. http://dx.doi.org/10.23967/exaqute.2022.3.04.

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This report presents the latest methods of optimisation under uncertainties investigated in the ExaQUte project, and their applications to problems related to civil and wind engineering. The measure of risk throughout the report is the conditional value at risk. First, the reference method is presented: the derivation of sensitivities of the risk measure; their accurate computation; and lastly, a practical optimisation algorithm with adaptive statistical estimation. Second, this method is directly applied to a nonlinear relaxation oscillator (FitzHugh–Nagumo model) with numerical experiments to demonstrate its performance. Third, the optimisation method is adapted to the shape optimisation of an airfoil and illustrated by a large-scale experiment on a computing cluster. Finally, the benchmark of the shape optimisation of a tall building under a turbulent flow is presented, followed by an adaptation of the optimisation method. All numerical experiments showcase the open-source software stack of the ExaQUte project for large-scale computing in a distributed environment.
7

Ayoul-Guilmard, Q., F. Nobile, S. Ganesh, M. Nuñez, A. Kodakkal, R. Rossi, and C. Soriano. D6.4 Report on stochastic optimisation for unsteady problems. Scipedia, 2021. http://dx.doi.org/10.23967/exaqute.2021.2.003.

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This report brings together methodological research on stochastic optimisation and work on benchmark and target applications of the ExaQute project, with a focus on unsteady problems. A practical, general method for the optimisation of the conditional value at risk is proposed. Three different optimisation problems are described: an oscillator problem selected as a suitable trial and illustration case; the shape optimisation of an airfoil, chosen as a benchmark application in the project; the shape optimisation of a tall building, which is the challenging target application set for ExaQUte. For each problem, the current developments and results are presented, the application of the proposed method is discussed, and the work to be done until the end of the project is laid out.
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Ayoul-Guilmard, Q., S. Ganesh, F. Nobile, R. Rossi, and C. Soriano. D6.3 Report on stochastic optimisation for simple problems. Scipedia, 2021. http://dx.doi.org/10.23967/exaqute.2021.2.001.

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This report addresses the general matter of optimisation under uncertainties, following a previous report on stochastic sensitivities (deliverable 6.2). It describes several theoretical methods, as well their application into implementable algorithms. The specific case of the conditional value at risk chosen as risk measure, with its challenges, is prominently discussed. In particular, the issue of smoothness – or lack thereof – is addressed through several possible approaches. The whole report is written in the context of high-performance computing, with concern for parallelisation and cost-efficiency.
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Li, Pengcheng, Bin Jia, and Hao Wang. BUCKLING BEHAVIOR AND OPTIMISATION ANALYSIS OF PRESTRESSED STAYED STEEL COLUMN. The Hong Kong Institute of Steel Construction, December 2018. http://dx.doi.org/10.18057/icass2018.p.060.

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CAEIRO, Maria Helena, Amílcar SOARES, Vasily DEMYANOV, and Mike CHRISTIE. Optimisation of a geostatistical non-stationary model in history matching. Cogeo@oeaw-giscience, September 2011. http://dx.doi.org/10.5242/iamg.2011.0260.

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