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Dos, Santos De Oliveira Rafael. "Bayesian Optimisation for Planning under Uncertainty." Thesis, The University of Sydney, 2018. http://hdl.handle.net/2123/20762.
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Under an increasing demand for data to understand critical processes in our world, robots have become powerful tools to automatically gather data and interact with their environments. In this context, this thesis addresses planning problems where limited prior information leads to uncertainty about the outcomes of a robot's decisions. The methods are based on Bayesian optimisation (BO), which provides a framework to solve planning problems under uncertainty by means of probabilistic modelling. As a first contribution, the thesis provides a method to find energy-efficient paths over unknown terrains. The method applies a Gaussian process (GP) model to learn online how a robot's power consumption varies as a function of its configuration while moving over the terrain. BO is applied to optimise trajectories over the GP model being learnt so that they are informative and energetically efficient. The method was tested in experiments on simulated and physical environments. A second contribution addresses the problem of policy search in high-dimensional parameter spaces. To deal with high dimensionality the method combines BO with a coordinate-descent scheme that greatly improves BO's performance when compared to conventional approaches. The method was applied to optimise a control policy for a race car in a simulated environment and shown to outperform other optimisation approaches. Finally, the thesis provides two methods to address planning problems involving uncertainty in the inputs space. The first method is applied to actively learn terrain roughness models via proprioceptive sensing with a mobile robot under localisation uncertainty. Experiments demonstrate the method's performance in both simulations and a physical environment. The second method is derived for more general optimisation problems. In particular, this method is provided with theoretical guarantees and empirical performance comparisons against other approaches in simulated environments.
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Morere, Philippe. "Bayesian Optimisation for Planning And Reinforcement Learning." Thesis, The University of Sydney, 2019. https://hdl.handle.net/2123/21230.
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This thesis addresses the problem of achieving efficient non-myopic decision making by explicitly balancing exploration and exploitation. Decision making, both in planning and reinforcement learning (RL), enables agents or robots to complete tasks by acting on their environments. Complexity arises when completing objectives requires sacrificing short-term performance in order to achieve better long-term performance. Decision making algorithms with this characteristic are known as non-myopic, and require long sequences of actions to be evaluated, thereby greatly increasing the search space size. Optimal behaviours need balance two key quantities: exploration and exploitation. Exploitation takes advantage of previously acquired information or high performing solutions, whereas exploration focuses on acquiring more informative data. The balance between these quantities is crucial in both RL and planning. This thesis brings the following contributions: Firstly, a reward function trading off exploration and exploitation of gradients for sequential planning is proposed. It is based on Bayesian optimisation (BO) and is combined to a non-myopic planner to achieve efficient spatial monitoring. Secondly, the algorithm is extended to continuous actions spaces, called continuous belief tree search (CBTS), and uses BO to dynamically sample actions within a tree search, balancing high-performing actions and novelty. Finally, the framework is extended to RL, for which a multi-objective methodology for explicit exploration and exploitation balance is proposed. The two objectives are modelled explicitly and balanced at a policy level, as in BO. This allows for online exploration strategies, as well as a data-efficient model-free RL algorithm achieving exploration by minimising the uncertainty of Q-values (EMU-Q). The proposed algorithms are evaluated on different simulated and real-world robotics problems, displaying superior performance in terms of sample efficiency and exploration.
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Marchant, Matus Roman. "Bayesian Optimisation for Planning in Dynamic Environments." Thesis, The University of Sydney, 2015. http://hdl.handle.net/2123/14497.
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This thesis addresses the problem of trajectory planning for monitoring extreme values of an environmental phenomenon that changes in space and time. The most relevant case study corresponds to environmental monitoring using an autonomous mobile robot for air, water and land pollution monitoring. Since the dynamics of the phenomenon are initially unknown, the planning algorithm needs to satisfy two objectives simultaneously: 1) Learn and predict spatial-temporal patterns and, 2) find areas of interest (e.g. high pollution), addressing the exploration-exploitation trade-off. Consequently, the thesis brings the following contributions: Firstly, it applies and formulates Bayesian Optimisation (BO) to planning in robotics. By maintaining a Gaussian Process (GP) model of the environmental phenomenon the planning algorithms are able to learn the spatial and temporal patterns. A new family of acquisition functions which consider the position of the robot is proposed, allowing an efficient trajectory planning. Secondly, BO is generalised for optimisation over continuous paths, not only determining where and when to sample, but also how to get there. Under these new circumstances, the optimisation of the acquisition function for each iteration of the BO algorithm becomes costly, thus a second layer of BO is included in order to effectively reduce the number of iterations. Finally, this thesis presents Sequential Bayesian Optimisation (SBO), which is a generalisation of the plain BO algorithm with the goal of achieving non-myopic trajectory planning. SBO is formulated under a Partially Observable Markov Decision Process (POMDP) framework, which can find the optimal decision for a sequence of actions with their respective outcomes. An online solution of the POMDP based on Monte Carlo Tree Search (MCTS) allows an efficient search of the optimal action for multistep lookahead. The proposed planning algorithms are evaluated under different scenarios. Experiments on large scale ozone pollution monitoring and indoor light intensity monitoring are conducted for simulated and real robots. The results show the advantages of planning over continuous paths and also demonstrate the benefit of deeper search strategies using SBO.
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Dowie, Tracy Ann. "A disassembly planning and optimisation methodology for design." Thesis, Manchester Metropolitan University, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.283082.
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Gregory, Christine. "Robust optimisation and its application to portfolio planning." Thesis, Brunel University, 2009. http://bura.brunel.ac.uk/handle/2438/3638.
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Decision making under uncertainty presents major challenges from both modelling and solution methods perspectives. The need for stochastic optimisation methods is widely recognised; however, compromises typically have to be made in order to develop computationally tractable models. Robust optimisation is a practical alternative to stochastic optimisation approaches, particularly suited for problems in which parameter values are unknown and variable. In this thesis, we review robust optimisation, in which parameter uncertainty is defined by budgeted polyhedral uncertainty sets as opposed to ellipsoidal sets, and consider its application to portfolio selection. The modelling of parameter uncertainty within a robust optimisation framework, in terms of structure and scale, and the use of uncertainty sets is examined in detail. We investigate the effect of different definitions of the bounds on the uncertainty sets. An interpretation of the robust counterpart from a min-max perspective, as applied to portfolio selection, is given. We propose an extension of the robust portfolio selection model, which includes a buy-in threshold and an upper limit on cardinality. We investigate the application of robust optimisation to portfolio selection through an extensive empirical investigation of cost, robustness and performance with respect to risk-adjusted return measures and worst case portfolio returns. We present new insights into modelling uncertainty and the properties of robust optimal decisions and model parameters. Our experimental results, in the application of portfolio selection, show that robust solutions come at a cost, but in exchange for a guaranteed probability of optimality on the objective function value, significantly greater achieved robustness, and generally better realisations under worst case scenarios.
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Dimopoulos, Christos. "Genetic programming for manufacturing optimisation." Thesis, University of Sheffield, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.327668.
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Rowbottom, Carl Graham. "Optimisation of beam-orientations in conformal radiotherapy treatment planning." Thesis, Institute of Cancer Research (University Of London), 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.314088.
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Haas, O. C. L. "Optimisation and control systems modelling in radiotherapy treatment planning." Thesis, Coventry University, 1997. http://curve.coventry.ac.uk/open/items/fc7aad2f-a43a-4045-adb0-9afa7e9033b3/1.
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Khwandah, Sinan. "System optimisation and radio planning for future LTE-advanced." Thesis, Brunel University, 2015. http://bura.brunel.ac.uk/handle/2438/13822.
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This work is related to wireless communication. In this Thesis three main issues are addressed for future cellular networks: power consumption, interference and mobility. These issues continue to be a burden on the system’s performance as long as technology keeps evolving. In the presented chapters, the focus was to introduce greater intelligence to the LTE system algorithms and bring to them a dynamic and self-organizing approach. The first approach concerns power consumption in wireless terminals. The currently applied solution to save energy is the DRX mechanism. It organizes the time when the terminal wakes up and starts receiving data, and when it goes into sleep mode in order to save its battery power. The current DRX is described as static or fixed which makes its parameters unsuitable for the nature of the bursty traffic. In this work an adaptive DRX mechanism is proposed and evaluated as the wireless terminal battery saving algorithm. The second approach is co-channel interference mitigation. To increase the system’s capacity and avoid spectrum scarcity, small cells such as Femtocells are deployed and operate on the same frequency bands as the Macrocell. Although these small nodes increase the system capacity, however, the challenges will be in the femtocells planning and management in addition to the interference issues. Here a dynamic interference cancellation approach is presented to enable the Femtocell to track the allocated resources to the Macro-users, and to avoid using them. The third approach concerns mobility management in heterogeneous networks. The wireless terminal may have different mobility levels during handover which increases the handover failures due to failure in handover commands and aging of the reported parameters. This issue is presented in detail with the aim to avoid performance degradation and improve the reporting mechanisms during fast mobility levels. For this regard the presented method proposes more cooperation between the serving cell and the end-user so that the large amount of overhead and measurement are reduced. Simulations with different configurations are conducted to present the results of the proposed models. Results show that the proposed models bring improvements to the LTE system. The enhanced self-organized architecture in the three presented approaches performs well in terms of power saving, dynamic spectrum utilization by Femtocells, and mitigation of sudden throughput degradation due to the serving cell’s downlink signal outage during mobility.
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Garmabdari, Rasoul. "Multi-Energy Microgrid Systems Planning and Energy Management Optimisation." Thesis, Griffith University, 2020. http://hdl.handle.net/10072/398878.
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Conventional power systems are predominantly composed of centralised large-scale generation sites that provide electricity to a large number of customers in a top-down unidirectional fashion and through transmission and distribution networks. To increase penetration of Renewable Energy Resources (RES) into this traditional power system and promotion of Distributed Energy Resources (DER) concept as an effective solution to deal with the challenges being faced in the conventional power system such as the energy losses, peak demand, peak generation, the infrastructure depreciation, and environmental effect, Microgrid (MG) concept is introduced. MG is defined as a locally controlled small unit of the power system that usually is in interaction with the main grid and is regarded as the building blocks of future Smart Grids (SGs). However, these systems are also capable of operating independently and isolated from the main grid, particularly in remote areas where access to the main grid is impossible or there is a disruptive event on the power system. The emergence of cutting-edge advances in the energy conversion and energy storage technologies and their commercial availability as well as introduction of various lucrative grid services that both grid and customers can benefit from derived the planners and engineers to further expand the flexibility, resilience and efficiency of MGs. To achieve this, Multi-Energy Microgrid System (MEMGS) concept as an expanded definition of MG was introduced to improve the efficiency of conventional energy systems, reduce air pollution as well as energy utilisation. MEMGS incorporates various energy technologies such as axillary boiler, gas turbine, RESs, thermal and battery energy storage systems that are fed by multiple energywares such as gas and electricity to supply multiple types of demands simultaneously such as electrical, heating and cooling loads. However, the integration of clusters of various technologies and concurrent delivery of different energy services causes additional complexities into the modelling and optimisation of these systems due to the potential interactions of energy vectors and various technologies at the consumer level.
The economic viability of MGs and MEMGSs rely on the configuration and operating management of the technologies. Therefore, is a need to develop an effective and efficient planning framework that can handle the interaction complexities and nonlinearities of the system, determining the most appropriate architecture, selecting the energy conversion and energy storage technologies and energy supply alternatives from a candidate pool. This thesis aims at addressing these challenges by initially developing a comprehensive and accurate dynamic model for MGs and MGESs components, investigating the technical and economic aspects, the nonlinear behaviour, maintenance and degradation phenomena, and uncertainties associated with technologies through Mixed-Integer Linear Programming (MILP) and Mixed Integer Quadratic Programming (MIQP). Then the established model is employed to establish and propose a multi-objective linearised planning optimisation approach. The architecture and choice of equipment of MEMGSs involve various elements such as availability and costs of the energy sources and equipment, and characteristics of the energy demand. Considering these factors, the proposed strategy allocates the size of the components utilised in the MGs and EMMGSs while meeting the defined performance indices such as degradation factor, reliability and grid power fluctuations smoothing indices. Once, the configuration and capacity of components are optimally determined, efficient energy management is required. The last part of this research focuses on energy management system scheduling and optimisation where the EMS scheduling module for MGs and MEMGSs are inspected considering the Time of Use tariff, peak shaving and valley filling functions, degradation of energy storage devices, along with the operating criteria and cost of the energy conversion units. Moreover, a real-time EMS solution is provided to deal with intermittent behaviour of RESs while participating in arbitrage market. The real-time EMS manages the energy flow optimally according to the acquired real-time data and its deviation from the original schedule attained in the scheduling optimisation stage. The primary objective of the EMS module development is to maximise profit while improving the performance of the MEMGSs. Throughout this research, the MILP and MIQP optimisation approach is adopted to achieve a fast convergence while avoiding complexity and long computation time that would cause due to the nonlinear behaviour and complex interaction of the technologies. Finally, having a practical insight into the challenges and concerns with connection adjacent MGs in distribution networks, an efficient centralised EMS optimisation framework is proposed to cope with the limitations and optimise the performance of the system, considering power losses, voltage deviations and nonlinear degradation of the components. The primary objective of this section of research is to achieve the optimal techno-economic solution.<br>Thesis (PhD Doctorate)<br>Doctor of Philosophy (PhD)<br>School of Eng & Built Env<br>Science, Environment, Engineering and Technology<br>Full Text
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Ahern, Zeke Alexander. "Exact and approximate optimisation for strategic bus network planning." Thesis, Queensland University of Technology, 2020. https://eprints.qut.edu.au/206458/1/Zeke_Ahern_Thesis.pdf.
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This thesis contributes to the area of transportation network design at the strategic level, considering objectives for the passenger and operator. The main goal of the research is to improve the existing methods by developing new and more rigorous approaches to integrating route choice, service frequency and adequately accounting for passenger waiting time. An exact model was developed: providing a concise non-ambiguous description to the problem. Case study problem instances found that exact methods implemented by commercial solvers are not scalable for practical problems. Therefore, meta-heuristics were presented to find near-optimal solutions efficiently and demonstrate the practicality of the model in the real-world.
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Palmer, Gareth John. "An integrated approach to manufacturing planning : optimisation in process planning and job shop scheduling." Thesis, University of Huddersfield, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.241154.
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Within manufacturing, increasing interest in being placed in the possibilities of integrated process planning and scheduling. Separating these two related tasks can impose constraints, on the final schedule, which are both undesirable and unnecessary. These constraints arise from premature decisions regarding the allocation of manufacturing resources. By making use of flexible process plans, these decisions can be delayed until the most appropriate time: during scheduling. The decisions can then be made on the basis of objectives common to both tasks (such as the minimisation of manufacturing cost). This thesis outlines an approach to manufacturing planning which is based on a highly general formulation of the problem. This integrated process planning/scheduling problem can be viewed as a generalisation of process plan optimisation, a task which is also considered in detail. A novel approach to plan optimisation is proposed, which in turn forms the basis for integrated planning and scheduling. Some research into integrated planning/scheduling has been reported in the literature. However, researchers differ in the way they formulate the integrated task. This thesis therefore attempts to outline a general framework for the characterisation of integrated process planning and scheduling problems. This considers both the degree and representation of process plan flexibility, and also the level of detail at which the shop floor is modelled. This framework forms a basis for a comparison of solution approaches. Published solution approaches are mostly based on the use of dispatching rules, but attempts have been made to use optimal search. The use of dispatching rules is essentially an ad hoc approach and, although relatively easy to apply in practice, produces solutions of mediocre quality. However, new research using simulated annealing suggests that neighbourhood search may offer a valuable alternative. This observation is supported by ambitious research published on the use of genetic algorithms. Because of the extreme combinatorial complexity of the combined task, optimal search methods are unlikely to be usable in practice. Furthermore, such methods exhibit a severe lack of generality because they make highly specific assumptions about problem formulation. Neighbourhood search techniques have inherent properties which give them a much higher level of generality. Although it is not an optimal search method, simulated annealing has been shown to provide solutions of significantly higher quality than those achieved by dispatching rule techniques. Also, and unlike optimal search techniques, it appears able to handle the immense complexity of the integrated planning/scheduling task. For the above reasons, it is argued that neighbourhood search techniques, such as simulated annealing, provide the best compromise available between solution quality and practical applicability.
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Wong, Sze Chun. "Phase-based optimisation of signal timings for area traffic control." Thesis, University College London (University of London), 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.262573.
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Ab, Rashid Mohd Fadzil Faisae. "Integrated multi-objective optimisation of assembly sequence planning and assembly line balancing using particle swarm optimisation." Thesis, Cranfield University, 2013. http://dspace.lib.cranfield.ac.uk/handle/1826/8257.
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In assembly optimisation, Assembly Sequence Planning (ASP) and Assembly Line Balancing (ALB) optimisations currently performed in serial, present an opportunity for integration, allowing benefits such as larger search space leading to better solution quality, reduced error rate in planning and fast time-to-market for a product. The literature survey highlights the research gaps, where the existing integrated ASP and ALB optimisation is limited to a Genetic Algorithm (GA) based approach, while Particle Swarm Optimisation (PSO) demonstrates better performance in individual ASP and ALB optimisation compared to GA. In addition, the existing works are limited to simple assembly line problems which run a homogeneous model on an assembly line. The aim of this research is to establish a methodology and algorithm for integrating ASP and ALB optimisation using Particle Swarm Optimisation. This research extends the problem type to integrated mixed-model ASP and ALB in order to generalise the problem. This research proposes Multi-Objective Discrete Particle Swarm Optimisation (MODPSO), to optimise integrated ASP and ALB. The MODPSO uses the Pareto-based approach to deal with the multi-objective problem and adopts a discrete procedure instead of standard mathematical operators to update its position and velocity. The MODPSO algorithm is tested with a wide range of problem difficulties for integrated single-model and mixed-model ASP and ALB problems. In order to supply sufficient test problems that cover a range of problem difficulties, a tuneable test problem generator is developed. Statistical tests on the algorithms’ performance indicates that the proposed MODPSO algorithm presents significant improvement in terms of larger non-dominated solution numbers in Pareto optimal, compared to comparable algorithms including GA based algorithms in both single-model and mixed-model ASP and ALB problems. The performance of the MODPSO algorithm is finally validated using artificial problems from the literature and real-world problems from assembly products.
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Avazpour, Abdoul Rasool. "The organisation and optimisation of domestic air transport services within Iran." Thesis, Loughborough University, 2001. https://dspace.lboro.ac.uk/2134/35239.
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Air transport is an important part of any major domestic transport system. Consequently significant insight, analysis and methodological effort is necessary to devise an analytical model of a domestic air transport network with a view to the optimisation. Since the advent of airline deregulation in the US in 1978, most domestic airlines have adopted a routing and scheduling strategy known as hub and spoke. The adoption of this system presents a major change to network planning and operations for most airlines. The hub and spoke system proposed in this dissertation is for developing countries and based on the domestic Iranian air transport network. The aim of the research is to devise a practical domestic air transport network system, capable of dealing with strategic aspects of network planning and evaluation.
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Wathne, Eivind. "Cargo Stowage Planning in RoRo Shipping : Optimisation Based Naval Architecture." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for marin teknikk, 2012. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-18597.
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Operations research has proven itself to be advantageous in several areas of the industry for many years, but is operations research a good approach to operational maritime planning? Expressions used to calculate the initial stability of a vessel are often non-linear. Optimisation models demand linearity, and approximated linearisations of the proven stability formulas needed to be developed. This was arguably found to be the biggest challenge when modelling the cargo stowage optimisation model. The characteristics of the RoRo shipping industry have been examined to gain a better understand of the segment. Further, some methods for calculating the initial stability of floating bodies have been presented for the readers that are not already familiar with this area of science.The thesis has used a published optimisation model as a foundation for further expansions. The model is a mathematical formulation of a cargo stowage problem in the RoRo shipping segment, where a predetermined vessel ships mandatory and optional cargoes from fixed loading ports to unloading ports. The reference model controls the vertical and transverse stability of the vessel by imposing constraints that are linear approximations of stability formulas. The model was expanded to ensure the longitudinal stability of the vessel as well. Additionally, the definitions of the existing vertical and transverse stability constraints were altered to provide more accurate co-ordinates for the expanded optimisation model.The computational study showed that the original model was able to find the optimal solution faster than the expanded model. The stowage flexibility was also better than for the expanded model, and the revenue generated was equal or higher in the original model for all scenarios. This was because the expanded model is of a greater size than the original, and is much more constrained in terms of stowage on the various decks. The expanded model divides the decks on the vessel not only into lanes, as the original model does, but also into slots. It can therefore ensure the longitudinal stability of the vessel as well. In addition to this, the lanes and slots in the expanded model are subject to lower and upper bounds for width and length, respectively. The original model allows the width of a lane to take values from zero up to the total width of the deck. In the original model, the size of the set of lanes therefore does not dictate the division of decks into lanes. This was found good for stowage flexibility, but is problematic to defend from a stability and safety perspective.
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Strouvalis, A. M. "Customised optimisation for the planning and scheduling of utility systems." Thesis, University of Manchester, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.505686.
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Al, Sobhi Khalil. "Planning and optimisation of relay-based cellular mobile wimax networks." Thesis, University of Newcastle Upon Tyne, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.500928.
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Despite the fact that advanced physical layer techniques, such as adaptive modulation and coding (AMC), and AAS (advanced antenna systems), are incorporated into mobile WiMAX systems, the roll-out and deployment of initial mobile WiMAX networks woria wide shows that some fundamental enhancements are needed to the current cellular architecture in order to meet the demand for networks that offer capacity, uniform coverage, and symmetrical user access. Moreover, the objective of any network operator is to minimise the capital expenditure of the initial network roll-out, while at the same time preserve the current network investment so as to ensure fast network deployment. For these reasons, the concept of radio relay deployment has emerged as a very 3nomical and efficient technique to boost system capacity and coverage.
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Vernon, Anthony Michael. "Network planning and optimisation for adaptive antenna base station systems." Thesis, University of Bristol, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.368721.
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Koleva, M. N. "Optimisation methodologies for the design and planning of water systems." Thesis, University College London (University of London), 2018. http://discovery.ucl.ac.uk/10046815/.
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This thesis addresses current topics of design and planning of water systems from water treatment units to a country-wide resources management schemes. The methodologies proposed are presented as models and solution approaches using mathematical programming, and mixed integer linear (MILP) and non-linear (MINLP) programming techniques. In Part I of the thesis, a synthesis problem for water treatment processes using superstructure optimisation is studied. An MINLP model is developed for the minimisation of water production cost considering physicochemical properties of water and operating conditions of candidate technologies. Next, new alternative path options are introduced to the superstructure. The resulting MINLP model is then partially linearised (plMINLP) and also presented as a mixed integer linear fractional programming (MILFP) model in order to improve the convergence of the optimisation model. Various linearisation and approximation techniques are developed. As a solution procedure to the fractional model, a variation of the Dinkelbach's algorithm is proposed. The models are tested on theoretical examples with industrial data. In Part II, an optimisation approach formulated as a spatially-explicit multi-period MILP model is proposed for the design of planning of water resources at regional and national scales. The optimisation framework encompasses decisions such as installation of new purification plants, capacity expansion, trading schemes among regions and pricing, and water availability under climate change. The objective is to meet water demand while minimising the total cost associated with developing and operating the water supply chain. Additionally, a fair trade-o between the total cost and reliability of the supply chain is incorporated in the model. The solution method is applied based on game theory using the concept of Nash equilibrium. The methodology is implemented on a case study based on Australian water management systems.
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Tavakoli, Siamak. "A generic predictive information system for resource planning and optimisation." Thesis, Brunel University, 2010. http://bura.brunel.ac.uk/handle/2438/8116.
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The purpose of this research work is to demonstrate the feasibility of creating a quick response decision platform for middle management in industry. It utilises the strengths of current, but more importantly creates a leap forward in the theory and practice of Supervisory and Data Acquisition (SCADA) systems and Discrete Event Simulation and Modelling (DESM). The proposed research platform uses real-time data and creates an automatic platform for real-time and predictive system analysis, giving current and ahead of time information on the performance of the system in an efficient manner. Data acquisition as the backend connection of data integration system to the shop floor faces both hardware and software challenges for coping with large scale real-time data collection. Limited scope of SCADA systems does not make them suitable candidates for this. Cost effectiveness, complexity, and efficiency-orientation of proprietary solutions leave space for more challenge. A Flexible Data Input Layer Architecture (FDILA) is proposed to address generic data integration platform so a multitude of data sources can be connected to the data processing unit. The efficiency of the proposed integration architecture lies in decentralising and distributing services between different layers. A novel Sensitivity Analysis (SA) method called EvenTracker is proposed as an effective tool to measure the importance and priority of inputs to the system. The EvenTracker method is introduced to deal with the complexity systems in real-time. The approach takes advantage of event-based definition of data involved in process flow. The underpinning logic behind EvenTracker SA method is capturing the cause-effect relationships between triggers (input variables) and events (output variables) at a specified period of time determined by an expert. The approach does not require estimating data distribution of any kind. Neither the performance model requires execution beyond the real-time. The proposed EvenTracker sensitivity analysis method has the lowest computational complexity compared with other popular sensitivity analysis methods. For proof of concept, a three tier data integration system was designed and developed by using National Instruments’ LabVIEW programming language, Rockwell Automation’s Arena simulation and modelling software, and OPC data communication software. A laboratory-based conveyor system with 29 sensors was installed to simulate a typical shop floor production line. In addition, EvenTracker SA method has been implemented on the data extracted from 28 sensors of one manufacturing line in a real factory. The experiment has resulted 14% of the input variables to be unimportant for evaluation of model outputs. The method proved a time efficiency gain of 52% on the analysis of filtered system when unimportant input variables were not sampled anymore. The EvenTracker SA method compared to Entropy-based SA technique, as the only other method that can be used for real-time purposes, is quicker, more accurate and less computationally burdensome. Additionally, theoretic estimation of computational complexity of SA methods based on both structural complexity and energy-time analysis resulted in favour of the efficiency of the proposed EvenTracker SA method. Both laboratory and factory-based experiments demonstrated flexibility and efficiency of the proposed solution.
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Levis, Aaron. "Multi-site capacity planning and business optimisation for process industries." Thesis, University College London (University of London), 2005. http://discovery.ucl.ac.uk/1444935/.
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Changing market conditions, volatile customer demand, intense competition and tightness of capital are some of the primary characteristics of the global economy that affect process industries nowadays. The main objective of the thesis is to facilitate business decision-making in today's increasingly complex and highly uncertain market environment by applying mathematical programming techniques for multi-site capacity planning and business optimisation in process industries. In the first part of the thesis, the problem of multi-site capacity planning under uncertainty in the pharmaceutical industry is addressed. A comprehensive two-stage, multi-scenario mixed-integer linear programming (MILP) model is proposed able to determine an optimal product portfolio and multi-site investment plan in the face of clinical trials uncertainty. A hierarchical algorithm is also developed in order to reduce the computational effort needed for the solution of the resulting large-scale MILP model. The applicability of the proposed solution methodology is demonstrated by a number of illustrative examples. The second part addresses the problem of business optimisation for customer demand management in process industries. A customer demand forecasting approach is developed based on support vector regression analysis. The proposed three-step algorithm is able to extract the underlying customer demand patterns from historical sales data and derive an accurate forecast as demonstrated through a number of illustrative examples. An active demand management approach for close substitute products is also developed based on price optimisation. The proposed methodology is able to determine optimal pricing policies as well as output levels, while taking into consideration manufacturing costs, resource availability, customer demand elasticity, outsourcing and market competition. An iterative algorithm is developed able to determine Nash equilibrium in prices for competing companies as demonstrated by the illustrative examples.
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Glorieux, Emile. "Multi-Robot Motion Planning Optimisation for Handling Sheet Metal Parts." Doctoral thesis, Högskolan Väst, Avdelningen för produktionssystem (PS), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:hv:diva-10947.
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Motion planning for robot operations is concerned with path planning and trajectory generation. In multi-robot systems, i.e. with multiple robots operating simultaneously in a shared workspace, the motion planning also needs to coordinate the robots' motions to avoid collisions between them. The multi-robot coordination decides the cycle-time for the planned paths and trajectories since it determines to which extend the operations can take place simultaneously without colliding. To obtain the quickest cycle-time, there needs to bean optimal balance between, on the one hand short paths and fast trajectories, and on the other hand possibly longer paths and slower trajectories to allow that the operations take place simultaneously in the shared workspace. Due to the inter-dependencies, it becomes necessary to consider the path planning, trajectory generation and multi-robot coordination together as one optimisation problem in order to find this optimal balance.This thesis focusses on optimising the motion planning for multi-robot material handling systems of sheet metal parts. A methodology to model the relevant aspects of this motion planning problem together as one multi-disciplinary optimisation problem for Simulation based Optimisation (SBO) is proposed. The identified relevant aspects include path planning,trajectory generation, multi-robot coordination, collision-avoidance, motion smoothness, end-effectors' holding force, cycle-time, robot wear, energy efficiency, part deformations, induced stresses in the part, and end-effectors' design. The cycle-time is not always the (only) objective since it is sometimes equally/more important to minimise robot wear, energy consumption, and/or part deformations. Different scenarios for these other objectives are therefore also investigated. Specialised single- and multi-objective algorithms are proposed for optimising the motion planning of these multi-robot systems. This thesis also investigates how to optimise the velocity and acceleration profiles of the coordinated trajectories for multi-robot material handling of sheet metal parts. Another modelling methodology is proposed that is based on a novel mathematical model that parametrises the velocity and acceleration profiles of the trajectories, while including the relevant aspects of the motion planning problem excluding the path planning since the paths are now predefined.This enables generating optimised trajectories that have tailored velocity and acceleration profiles for the specific material handling operations in order to minimise the cycle-time,energy consumption, or deformations of the handled parts.The proposed methodologies are evaluated in different scenarios. This is done for real world industrial case studies that consider the multi-robot material handling of a multi-stage tandem sheet metal press line, which is used in the automotive industry to produce the cars' body panels. The optimisation results show that significant improvements can be obtained compared to the current industrial practice.
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Egena, O. "Planning and optimisation of 4G/5G mobile networks and beyond." Thesis, University of Salford, 2018. http://usir.salford.ac.uk/45123/.
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As mobile networks continue to evolve, two major problems have always existed that greatly affect the quality of service that users experience. These problems are (1) efficient resource management for users at the edge of the network and those in a network coverage hole. (2) network coverage such that improves the quality of service for users while keeping the cost of deployment very low. In this study, two novel algorithms (Collaborative Resource Allocation Algorithm and Memetic-Bee-Swarm Site Location-Allocation Algorithm) are proposed to solve these problems. The Collaborative Resource Allocation Algorithm (CRAA) is inspired by lending and welfare system from the field of political economy and developed as a Market Game. The CRAA allows users to collaborate through coalition formation for cell edge users and users with less than the required Signal-to-Noise-plus-Interference-Ratio to transmit at satisfactory Quality of Service, which is a result of the payoff, achieved and distributed using the Shapley value computed using the Owens Multi Linear Extension function. The Memetic-Bee-Swarm Site Location-Allocation Algorithm (MBSSLAA) is inspired by the behaviour of the Memetic algorithm and Bee Swarm Algorithm for site location. Series of System-level simulations and numerical evaluations were run to evaluate the performance of the algorithms. Numerical evaluation and simulations results show that the Collaborative Resource Allocation Algorithm compared with two popular Long Term Evolution-Advanced algorithms performs higher in comparison when assessed using throughput, spectral efficiency and fairness. Also, results from the simulation of MBSSLAA using realistic network design parameter values show significant higher performance for users in the coverage region of interest and signifies the importance of the ultra-dense small cells network in the future of telecommunications’ services to support the Internet of Things. The results from the proposed algorithms show that following from the existing solutions in the literature; these algorithms give higher performance than existing works done on these problems. On the performance scale, the CRAA achieved an average of 30% improvement on throughput and spectral efficiency for the users of the network. The results also show that the MBSSLAA is capable of reducing the number of small cells in an ultra-dense small cell network while providing the requisite high data coverage. It also indicates that this can be achieved while maintaining high SINR values and throughput for the users, therefore giving them a satisfactory level of quality of service which is a significant requirement in the Fifth Generation network’s specification.
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Rögnvaldsson, Kristján Óttar. "Multi-Objective Mixed-Integer Linear Optimisation of Aircraft Load Planning." Thesis, KTH, Optimeringslära och systemteori, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-253363.
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A general multi-objective optimisation model is developed for the load planning decision process of a bulk loaded commercial aircraft, using the Airbus A321 fitted with additional fuel tanks as a baseline platform. The model’s input is a specific set of load items, with associated quantities, mass and volume. The output is a load plan, stating where each item should be loaded and in what quantity. The load plans should be optimal with respect to a target centre of gravity range and handling efficiency. Furthermore, the solutions should be robust with respect to perturbations in the input data. Three objective functions and a set of constraints are defined to achieve this task. A constraint that ensures the ground stability of the aircraft is developed and analysed. A lexicographic approach is used solve the multi-objective problem, by sequentially solving a set of mixed-integer linear programs. The sequence is determined from a priority ranking of the objectives. Testing is carried out with data from an operator of the A321, with four different test cases. Test results indicate that the model is capable of solving the load planning problem for the baseline aircraft. The centre of gravity values are within the optimal range, and the load distributions are efficient. Additional margins on aircraft limits assist with maintaining feasibility in case of input perturbation. The model is also robust with respect to the highly variable test data. The main causes of infeasibility are mixing constraints and additional balance envelope margins. The ground stability constraint does not cause any significant amount of infeasibilities, and primarily increases the safety level of the load plans. A strength of the model is its relatively simple handling of the multiple objectives, and the small number of tunable parameters also makes the model controllable. A trained agent in the industry is able to understand and control the model without an extensive technical background. The test process used differs slightly from the actual industry load planning process. As a result, testing only allows for evaluation of the model’s ability to solve the load planning problem, and gives no justification for implementation in real-world operations. Such an evaluation requires a prototype to be tested in an operational environment using the actual process. As testing was only done for the baseline aircraft, with one set of test data and model parameters, a justifiable conclusion cannot be reached on the model’s applicability to other bulk loaded aircraft. Therefore, it is recommended to carry out further testing on different aircraft as the next step in them model’s evaluation. iv<br>En allmänn flermåls optimeringsmodell utvecklas för besluttsprocessen relaterat till lastning av ett kommersiellt flygplan, som använder Airbus A321 utrustad med ytterligare bränslestankar som en bas. Modellens indata är ett specifikt set av artiklar som ska lastas tillsammans med information om mängd, tyngd och volym. Utvärdet är en beskrivande plan som visar var varje artikel ska lastas och i vilken mängd. Planen ska vara optimal med hänsyn till ett specifikt tyngdpunkts intervall och vara effectiv för lastningsoperationer. Dessutom ska den vara robust med hänsyn till störningar i indatan. Tre målfunktioner tillsammans med ett set av begränsningar används för att lösa problemet. En specifik begränsning som säkrar flygplanets stabilitet på grunden utvecklas och dess känslighet analyseras. En lexikografisk metod används för att lösa flermåls problemet, där lösar en sekvens av blandade heltalsprogrammer. Sekvensen är definierad ut från en prioritetsordning av de olika målfunktioner. Testning av modellen är utförd med indata från en operatör av A321 basflygplanet med fyra olika testfall. Testresultaten visar att modellen kan användas för att lösa lastningsproblemet för basflygplanet. Tyngdpunktsvärden är inom det optimal intervall och fördelningen av artiklar är effektiv. Extra marginaler på flygplansbegränsningar hjälper med att säkra lösningen under störningar på indatan. Modellen är också robust med hänsyn till högvarierad indata. Huvudorsaker till omöjliga testfall, de utan lösningar, är begränsningar på blandning av artiklar samt extra marginaler på flygplansbegränsningar. Begränsningen för grund stabilitet är inte en orsak till omöjlighet, och ökar primärt säkerhetsnivån på lösningen. En styrka till modellen är dess enkel hantering av de olika målfunktioner och de få parametrar gör modellen kontrollbar. En utbildad agent från industrin kan förstå och kontrollera modellen, utan att ha en teknisk bakgrund. Testprocessen som används representerar inte exakt industriprocessen. Testprocessen kan därför bara användas till att utvärdera modellens förmåga till att lösa lastningsproblemet, och ger ingen motivering på bruk i verkliga operationer. En utvärdering på den förmåga krävs en utveckling av en prototyp i verkliga världen. Testning av bara en typ av basflygplan, tillsammans med ett set av indata och modellparametrar, ger inte en grund till en konklusion på modellens tillämplighet för andra flygplan. Därför rekommenderas det att utföra ytterligare testning på andra flygplan som nästa steg i modellens utvärdering.
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Phangestu, Jimmi. "Optimisation Models for Medium-Long Term Logistics Planning in Mining." Thesis, Curtin University, 2017. http://hdl.handle.net/20.500.11937/57345.
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In the mining industry, the logistics planning problem involves a mining value chain that comprises stockpiles at multiple mines, a rail network, stockpiles at multiple ports, and shipping. The objective is to maximise the total material throughput subject to a range of operational and capacity restrictions. We develop and implement an effective computational model for solving this difficult large-scale problem. Testing on real case studies demonstrates the value of our methodology.
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Sinulingga, S. "Real time MRP with optimisation of manufacturing capacity utilisation." Thesis, Cranfield University, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.234523.
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ZORNADA, MICHELA. "A Methodological Approach to Support Car Sharing Planning." Doctoral thesis, Università degli Studi di Trieste, 2020. http://hdl.handle.net/11368/2963900.
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Negli ultimi anni stanno emergendo diverse soluzioni innovative di trasporto, potenzialmente atte a limitare il primato dell’auto privata; il car sharing è una di queste, sebbene presenti alcuni aspetti critici che, se trascurati, possono portare al fallimento del servizio. Tra i principali fattori che caratterizzano questo nuovo tipo di servizio di mobilità e ne influenzano il successo emergono, per citarne alcuni, la stretta relazione tra domanda e offerta, gli effetti sull’ambiente, la relazione con il trasporto pubblico, il tema economico per l’operatore e, non da ultimo, il fattore “novità” per i cittadini.
Riscontrata dalla letteratura la mancanza di una precisa fase progettuale, capace di tenere in considerazione tutti gli elementi cardine del sistema, il presente lavoro di ricerca si pone l’obiettivo di sviluppare un approccio metodologico globale e strutturato, in grado di supportare il progettista nella pianificazione di un nuovo servizio di car sharing, tenendo conto degli aspetti critici e delle loro mutue relazioni.
La metodologia sviluppata è di tipo “multi-step”, ovvero sono presenti diverse fasi che si basano ciascuna su diverse teorie e strumenti, quali, sondaggi alle preferenze dichiarate, modelli alle scelte discrete, processi di ottimizzazione, relazionati ed integrati tra loro poiché gli output di una fase sono gli input di quella successiva. Inoltre, un algoritmo, sviluppato per il dimensionamento degli elementi dell’offerta, è stato integrato in una delle fasi della procedura.
Al fine di avallarne le sue potenzialità, la metodologia è stata testata, contestualizzandola ad un caso di studio, mirato alla progettazione di un servizio serale di car sharing destinato agli studenti dell’Università degli Studi di Trieste. Da ciò si evince che la metodologia possa offrire un utile supporto al progettista, consentendogli di gestire il processo di pianificazione senza tralasciare aspetti importanti per il futuro successo del servizio, offrendo uno strumento semplice, flessibile ma allo stesso tempo accurato.
La ricerca mette in luce la complessità della pianificazione di un servizio di auto condivise e valuta gli strumenti necessari per migliorarla, evidenziando come i diversi aspetti della progettazione vadano considerati in un’ottica integrata.<br>Over recent years, different innovative transport solutions are emerging with the potential for mitigating the primacy of private car. Car sharing is one of them, although it presents some critical aspects which can lead to the failure of the service if neglected. The mutual influence between demand and supply, environmental impacts, relationship with public transport, operator’s economic issue, as well as the “novelty” for citizens are some of the main factors which characterise this new mobility service and influence its success.
An intensive literature analysis reveals that a precise planning phase, able to consider all the critical aspects of the system, is lacking. This research work aims to develop a global and structured methodological approach, capable of supporting the designer in a new car sharing service planning, handling all the key aspects and their relationships.
The developed methodology is “multi-step”, i.e. there are several phases, based on different theories and tools such as stated preference survey, discrete choice model, optimisation process, which are related to each other since the outputs of a step are the inputs of the following one. Furthermore, an algorithm, developed for dimensioning the supply’s elements, is integrated into a phase of the suggested methodology.
The methodological approach is tested, applying it to the planning of a car sharing service dedicated to the University of Trieste students’ night trips. It transpires that the proposed procedure can be a reliable support for the planning process management, allowing the designer to consider all the aspects for the new service success, attesting to be a simple, flexible and accurate instrument.
This research provides evidence that car sharing planning is a complex process and defines a methodology which is expected to contribute to the definition of successful services. It also highlights how the different planning aspects are related and the importance of considering all of them jointly.
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Rusaw, Shawn. "Sensor-based motion planning via nonsmooth analysis." Thesis, University of Oxford, 2002. http://ora.ox.ac.uk/objects/uuid:46fa490d-c4ca-45ad-9cd5-b1f11920863d.
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In this thesis we present a novel approach to sensor-based motion planning developed using the mathematical tools provided by the field of nonsmooth analysis. The work is based on a broad body of background material developed using the tools of differential topology (smooth analysis), that is limited to simple cases like a point or circular robot. Nonsmooth analysis is required to extend this background work to the case of a polygonal robot moving amidst polygonal obstacles. We present a detailed nonsmooth analysis of the distance function for arbitrary configuration spaces and use this analysis to develop a planner for a rotating and translating polygonal mobile robot. Using the tools of nonsmooth analysis, we then describe a one-dimensional nonsmooth roadmap of the robot's freespace called the Nonsmooth Critical Set + Nonsmooth Generalised Voronoi Graph (NC<sub>RIT</sub>+NGVG) where the robot is equidistant to a number of obstacles, in a critical configuration or passing between two obstacles. We then use the related field of nonsmooth control theory to develop several provably stable control laws for following and exploring the nonsmooth roadmap. Finally, we implement a motion planner in simulation and for a real polygonal mobile robot, thus verifying the utility and practicality of the nonsmooth roadmap.
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Sandve, Kjell. "Cost analysis and optimal maintenance planning for monotone, repairable systems." Thesis, Robert Gordon University, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.336620.
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Rahmani, Nastaran. "Planning and routing via decomposition approaches." Thesis, Bordeaux, 2014. http://www.theses.fr/2014BORD0141/document.
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Problèmes de tournées de véhicules statiques et déterministes ne peuvent pas être utilisés dans de nombreux systémes de la vieréelle, du fait que les données d’entrée ne sont pas fiables et sont révélées au fil du temps. Dans cette thèse, nous étudions un problème de ramassage et de livraison avec fenêtres de temps et un maximum de temps de trajet - le problème dial-a-ride - dans sa variante statique et dynamique, et nous faisons des propositions spécifiques sur les modèles d’optimisation robustes pour résoudre ce problème. Pour résoudre le modèle statique, nous développons une approche branch-and-price qui gère toutes les contraintes detemps dans le processus de création d’itinéraires de véhicules. Notre travail est axé sur les techniques de résolution du sous-problème et d’accélération pour l’approche branch-and-price. Nos résultats numériques montrent que la méthode est compétitive par rapport aux approches existantes qui sont basées sur le branch-and-cut. Dans le contexte dynamique, où certaines données d’entrée sont révélées dynamiquement ou modifiées au fil du temps, nous appliquons notre algorithme branch-and-price pour la ré-optimisation dans une approche sur horizon glissant<br>Static and deterministic vehicle routing problems cannot be used in many real-life systems, as input data are not reliable and revealedover time. In this thesis, we study a pickup and delivery problem with time windows accounting for maximum ride time constraints – the so-called diala- ride problem – in its static and dynamic variant, and we make specific proposal on robust optimization models for this problem. To solve the static model, we develop a branch-and-price approach that handles ride time constraints in the process of generating feasible vehicle routes in the course of the optimization procedure. Our work is focussed on the pricing problem solver and acceleration techniques for the branch-and-price approach. Our numerical results show that the method is competitive compared to existing approaches that are based on branch-and-cut. In the dynamic context, where some input data are revealed or modified over time, we apply our branchand- price algorithm for re-optimization in a rolling horizon approach
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Moad, Kamel. "Modélisation et optimisation multi-niveaux du transport forestier." Thesis, Bordeaux, 2016. http://www.theses.fr/2016BORD0101/document.
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Cette thèse est une contribution à la modélisation, la planification et l’optimisation du transport pour l’approvisionnement en bois de forêt des industries de première transformation. Dans ce domaine, les aléas climatiques (mise au sol des bois par les tempêtes), sanitaires (attaques bactériologiques et fongiques des bois) et commerciaux (variabilité et exigence croissante des marchés) poussent les divers acteurs du secteur (entrepreneurs et exploitants forestiers, transporteurs) à revoir l’organisation de la filière logistique d’approvisionnement, afin d’améliorer la qualité de service (adéquation offre-demande) et de diminuer les coûts.L’objectif principal de cette thèse était de proposer un modèle de pilotage améliorant la performance du transport forestier, en respectant les contraintes et les pratiques du secteur.Les résultats établissent une démarche de planification hiérarchique des activités de transport à deux niveaux de décision, tactique et opérationnel. Au niveau tactique, une optimisation multi-périodes permet de répondre aux commandes en minimisant l’activité globale de transport, sous contrainte de capacité agrégée des moyens de transport accessibles. Ce niveau permet de mettre en oeuvre des politiques de lissage de charge et d’organisation de sous-traitance ou de partenariats entre acteurs de transport. Au niveau opérationnel, les plans tactiques alloués à chaque transporteur sont désagrégés, pour permettre une optimisation des tournées des flottes, sous contrainte des capacités physiques de ces flottes.Les modèles d’optimisation de chaque niveau sont formalisés en programmation linéaire mixte avec variables binaires. L’applicabilité des modèles a été testée en utilisant un jeu de données industrielles en région Aquitaine et a montré des améliorations significatives d’exploitation des capacités de transport par rapport aux pratiques actuelles.Les modèles de décision ont été conçus pour s’adapter à tout contexte organisationnel, partenarial ou non : la production du plan tactique possède un caractère générique sans présomption de l’organisation, celle-ci étant prise en compte, dans un deuxième temps, au niveau de l’optimisation opérationnelle du plan de transport de chaque acteur<br>The present manuscript tackles the supply chain forest transportation problem in the context of forestry primary industry. In this context, several risks may affect the forest supply chain: the unpredictable weather conditions (tree falling provoked by major storms); sanitary emergencies (tree pest and diseases); and, diverse commercial circumstances (the variability of market demands). The aforementioned issues motivate the diverse forest sector protagonists (entrepreneurs, forest operators and drivers) to seek support for improving their logistic operations. The aim of this effort is to improve the service quality (offer-demand agreement) diminishing in this way the total costs. Therefore, the main goal of this thesis is the proposal of a novel management model which improves forest-to-mill transport performance. At the same time, the proposed model accounts for the forest sector manners and constraints. The contribution of this thesis is threefold: first a transportation model is developed, later on the transport planning is managed, and finally an optimization procedure is proposed.The thesis results propose a hierarchical planning for the forestry transportation. Two decision levels are suggested: tactic and operational. At a tactic level, a multi-period optimization is considered. The multi-period optimization strategy meets the customer supply demands while minimizes the global transportation activity. Such strategy takes into account the restrictions of the total available transportation means. Moreover, at this level the activity balancing politics may be developed, as well as subcontractors coordination between transport companies. On the other hand, at the operational level, the tactic planning assigned for each transporter is divided so an optimization of the fleet’s transport assignation is done considering the vehicles constraints.The decision process is modelled as a Mixed Linear Programming formulation. The application considers a data set coming from the industry settled at the Aquitaine region in France. The results have shown a significant improvement on the transport capabilities with respect to the conventional transport practices.It is worth to mention that the decision models were designed such that they may be adapted to different context either collaborative or not. In both cases, the tactic planning has a generic purpose, in other words, it is independent of the kind of organization involved, whereas specific organizations are taken into account when planning actors’ activities at the operational level
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Rojas, Villabona Alvaro Alexander. "Optimisation of planning and delivery methods for Gamma Knife Stereotactic Radiosurgery." Thesis, University College London (University of London), 2018. http://discovery.ucl.ac.uk/10048270/.
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The work presented in this dissertation is the response to a series of technical and clinical challenges encountered during the first four years of operations in the Gamma Knife Centre at Queen Square. These challenges, which are common to most contemporary Gamma Knife centres, were prospectively addressed and practical solutions were developed for the questions they posed. The dosimetric differences between the new convolution algorithm and the standard TMR 10 algorithm traditionally used for prediction of dose distribution in Gamma Knife Radiosurgery (GKR) were explored. It was demonstrated that inhomogeneity correction with the convolution algorithm results in a considerable but consistent dose shift compared to TMR 10. No significant difference in relative dose distribution was noted and it was concluded that a reduction of the prescription dose is necessary to obtain the same absolute dosimetric effect with the convolution algorithm. The stability of the stereotactic Leksell frame G in GKR was demonstrated using a comprehensive study design that involved repeated measurements of landmarks by two observers. The study provided reliable and realistic evidence of submillimetre stability of the stereotactic frame throughout the treatment procedure which is important for evaluation and development of new frameless radiosurgery systems. The technical feasibility of using a combination of three magnetic resonance angiography sequences (triple-MRA), instead of digital subtraction angiography (DSA), for visualisation and delineation of brain Arteriovenous Malformations (AVMs) for GKR targeting was demonstrated. Target volumes obtained using triple-MRA are on average 10% smaller than AVM targets obtained with the standard DSA planning method and this can potentially reduce the risk of adverse radiation effects (ARE). The treatment planning method described here has laid the way for a change in clinical practice that favours a less invasive treatment planning approach. The same principle of less invasive AVM imaging with triple-MRA was used at the post-GKR stage, when a DSA is performed to confirm AVM obliteration. Triple-MRA was found to consistently confirm or rule out residual AVMs in patients who had undergone GKR for brain AVMs, compared to DSA, and it can also be reliably used for characterisation of residual AVMs. The use of triple-MRA as a first line for assessment of obliteration after GKR is recommended.
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Ionescu, Stefan, and Kaj Jonsson. "Design Trade-offs in Optimisation Based Trajectory Planning for Autonomous Racing." Thesis, KTH, Mekatronik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254448.
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The autonomous vehicle industry is fast developing with many companies vying to release the first fully autonomous passenger vehicle. However, the advancement of the field also drives forward related areas such as autonomous racing. This paper aims to investigate how to optimally control an autonomous race car such that its progression across a previously unknown race track is maximised. This paper is inspired by the Formula Student race. The paper investigates using a Model Predictive Controller, MPC, to convert current vehicle position to a set of control inputs through the use of a vehicle model. Two different models have been investigated, the first focusing purely on the kinematics of the system, whilst the second encodes tyre forces for a dynamic approach. Further, the planning horizon of the MPC has been investigated to see how changes to it affect the performance of the controller and thus obtain insight into the trade-off between model complexity and planning horizon. Finally the limitations of both models was investigated. A modular real time implementation has been developed with the help of The CT Toolbox, a fast, C++ based, MPC implementation control toolbox. Small track segments and a full track have been used to evaluate the performance between the two models. Results showed that the computational difference from a more complex model is not a major limiting factor for the update rate of the MPC. However, the performance of the two models was significantly different with the dynamic based MPC far outperforming the kinematic. Constraining lateral accelerations of the car is critical when designing the controller as failure to do so will allow the controller to plan unfeasible paths. The dynamic model, through encoding the tyre forces, accomplishes this successfully completing the lap. However, the kinematic model, which assumes zero slip, fails as the speed gets high with sharp corners. It was also found that too short planning horizons do not allow sufficient information to flow to the controller causing poor trajectories. As one increases the planning horizon, diminishing returns appear as computational complexity increases with little improvements to the trajectory from the extra information. Finally it was found that sharp corners especially when chained together caused the most performance issues, however given an appropriate planning horizon, the dynamic model handles them well proposing a path similar to that of professional drivers. The paper outlines related works in the autonomous racing field, and gives an overview of the theory behind MPC. The focus then shifts onto how the system was setup, including the necessary theory, with an indepth look at the system architecture.<br>Utvecklingen inom autonoma fordon är idag ett område som snabbt går framåt. Företag kämpar med att vara först ut på marknaden med full autonom styrning för fordon. Genom denna utveckling utforskas även närliggande områden, såsom racing. Arbetet kommer att fokusera på hur en autonom bil kan maximera hastigheten på en bana. Närmare bestämt optimal reglering för en autonom racing-bil. Arbetet har inspirerats av tävlingen Formula Student race, som är en tävling mellan universitet världen över. En modellbaserad kontrollstrategi implementeras, Model Predictive Control (MPC), som genom att modellera bilens dynamik tar beslut om bilens agerande. I arbetet så har två bilmodeller implementerats och jämförts. En kinematisk modell, där bilens agerande kan beskrivas med geometriska samband. Samt en dynamisk modell, som även tar hänsyn till de dynamiska sambanden som ges av bilens däck. Vidare så har olika tidshorisonter för kontrollern analyserats. Då både modellkomplexitet och tidshorisont ger ett negativt anspråk på beräkningstid, undersöks den avvägning som uppstår mellan varierande komplexitet hos modell vägt mot längd på tidshorisont. Slutligen så har det undersökts vilka begränsningar som är förknippade med modellerna. Implementering har gjorts med CT Toolbox, ett tidseffektivt C++ baserad ramverk för MPC styrning. Implementationen har sedan utvärderats genom att undersöka prestationen för modellerna på olika bansegment. Resultatet visade att skillnaden i beräkningstid för de två modellerna ej var en stor faktor för uppdateringsfrekvensen. Prestationen för de två modellerna visade sig skilja signifikant. I och med möjligheten att begränsa accelerationen i sidled för den dynamiska modellen kunde bilen justera hastigheten i kurvor, till skillnad ifrån den kinematiska modeller, där antagande om perfekt grepp gjorts. Undersökningen visade även att vid för kort tidshorisont, får kontrollern ej tillräckligt med nödvändig information, vilket resulterar i bristande planering. Vid ökning av tidshorisont, ökar beräkningstiden. Det påverkar prestandan positivt, men bara till en viss nivå, då för mycket information ej är tillämpbar av kontrollern. Detta arbete använder sig av tidigare gjord forskning inom autonoma racing-fordon, och ger en övergripande teori inom styrning med hjälp av MPC. Arbetet skiftar sedan till att implementera ett autonomt system vad gäller planering och styrning. Slutligen presenteras resultaten och en medföljande diskussion med förslag på hur detta kan förbättras vid framtida implementation.
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Dubedout, Hugues. "Supply chain design and distribution planning under supply uncertainty : Application to bulk liquid gas distribution." Phd thesis, Ecole des Mines de Nantes, 2013. http://tel.archives-ouvertes.fr/tel-00910097.
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The distribution of liquid gazes (or cryogenic liquids) using bulks and tractors is a particular aspect of a fret distribution supply chain. Traditionally, these optimisation problems are treated under certainty assumptions. However, a large part of real world optimisation problems are subject to significant uncertainties due to noisy, approximated or unknown objective functions, data and/or environment parameters. In this research we investigate both robust and stochastic solutions. We study both an inventory routing problem (IRP) and a production planning and customer allocation problem. Thus, we present a robust methodology with an advanced scenario generation methodology. We show that with minimal cost increase, we can significantly reduce the impact of the outage on the supply chain. We also show how the solution generation used in this method can also be applied to the deterministic version of the problem to create an efficient GRASP and significantly improve the results of the existing algorithm. The production planning and customer allocation problem aims at making tactical decisions over a longer time horizon. We propose a single-period, two-stage stochastic model, where the first stage decisions represent the initial decisions taken for the entire period, and the second stage representing the recovery decision taken after an outage. We aim at making a tool that can be used both for decision making and supply chain analysis. Therefore, we not only present the optimized solution, but also key performance indicators. We show on multiple real-life test cases that it isoften possible to find solutions where a plant outage has only a minimal impact.
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Simmonds, Christopher Martin. "Soft handover parameter optimisation for DS-CDMA downlink design." Thesis, University of Bristol, 1995. http://hdl.handle.net/1983/471bc894-d62f-4db5-98a8-19b2fc537f55.
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Burgon, Ross. "Manoeuvre Planning Architecture for the Optimisation of Spacecraft Formation Flying Reconfiguration Manoeuvres." Thesis, Cranfield University, 2010. http://dspace.lib.cranfield.ac.uk/handle/1826/4567.
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Formation flying of multiple spacecraft collaborating toward the same goal is fast
becoming a reality for space mission designers. Often the missions require the spacecraft to
perform translational manoeuvres relative to each other to achieve some mission objective.
These manoeuvres need to be planned to ensure the safety of the spacecraft in the formation
and to optimise fuel management throughout the fleet. In addition to these requirements is it
desirable for this manoeuvre planning to occur autonomously within the fleet to reduce
operations cost and provide greater planning flexibility for the mission. One such mission that
would benefit from this type of manoeuvre planning is the European Space Agency’s
DARWIN mission, designed to search for extra-solar Earth-like planets using separated
spacecraft interferometry.
This thesis presents a Manoeuvre Planning Architecture for the DARWIN mission. The
design of the Architecture involves identifying and conceptualising all factors affecting the
execution of formation flying manoeuvres at the Sun/Earth libration point L2. A systematic
trade-off analysis of these factors is performed and results in a modularised Manoeuvre
Planning Architecture for the optimisation of formation flying reconfiguration manoeuvres.
The Architecture provides a means for DARWIN to autonomously plan manoeuvres during
the reconfiguration mode of the mission. The Architecture consists of a Science Operations
Module, a Position Assignment Module, a Trajectory Design Module and a Station-keeping
Module that represents a multiple multi-variable optimisation approach to the formation
flying manoeuvre planning problem. The manoeuvres are planned to incorporate target
selection for maximum science returns, collision avoidance, thruster plume avoidance,
manoeuvre duration minimisation and manoeuvre fuel management (including fuel
consumption minimisation and formation fuel balancing). With many customisable variables
the Architecture can be tuned to give the best performance throughout the mission duration.
The implementation of the Architecture highlights the importance of planning formation
flying reconfiguration manoeuvres. When compared with a benchmark manoeuvre planning
strategy the Architecture demonstrates a performance increase of 27% for manoeuvre
scheduling and fuel savings of 40% over a fifty target observation tour.
The Architecture designed in this thesis contributes to the field of spacecraft formation
flying analysis on various levels. First, the manoeuvre planning is designed at the mission
level with considerations for mission operations and station-keeping included in the design.
Secondly, the requirements analysis and implementation of Science Operation Module
represent a unique insight into the complexity of observation scheduling for exo-planet
analysis missions and presents a robust method for autonomously optimising that scheduling.
Thirdly, in-depth analyses are performed on DARWIN-based modifications of existing
manoeuvre optimisation strategies identifying their strengths and weaknesses and ways to
improve them. Finally, though not implemented in this thesis, the design of a Station-keeping
Module is provided to add station-keeping optimisation functionality to the Architecture.
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Gun, Philip. "Multi Vehicle Trajectory Planning On Road Networks." Thesis, University of Sydney, 2020. https://hdl.handle.net/2123/25389.
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When multiple autonomous vehicles work in a shared space, such as in a surface mine or warehouse, they often travel along specified paths through a static road network. Although these vehicles’ actions and performance are coupled, their motion is often planned myopically or omits cooperation beyond avoiding collisions reactively. More desirable solutions could be achieved by coordinating and planning actions ahead of time.
To make multi-vehicle systems more productive and efficient, the thesis introduces planning methods that can optimise for travel time, energy consumption, and trajectory smoothness. Vehicle motion is coordinated by using motion models that combine all trajectories, and avoid collisions. Mathematical programming is then used to find optimised solutions. The proposed methods are shown to significantly reduce solution costs compared to an approach based on common driving practices.
As the number of vehicles and interactions between them increases, the number of solutions grows exponentially, making finding a solution computationally challenging. A major aim here was to find high quality solutions within practical computation times. To achieve this, techniques were developed that exploit the structure of the problems. This includes a heuristic algorithm that scales better with problem size, and is combined with the mathematical programming techniques to reduce their complexity. These were found to significantly reduce computation times, trading off marginal solution quality.
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McGowan, Stacey Elizabeth. "Incorporating range uncertainty into proton therapy treatment planning." Thesis, University of Cambridge, 2015. https://www.repository.cam.ac.uk/handle/1810/248787.
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This dissertation addresses the issue of robustness in proton therapy treatment planning for cancer treatment. Proton therapy is considered to be advantageous in treating most childhood cancers and certain adult cancers, including those of the skull base, spine and head and neck. Protons, unlike X-rays, have a finite range highly dependent on the electron density of the material they are traversing, resulting in a steep dose gradient at the distal edge of the Bragg peak. These characteristics, together with advancements in computation and technology have led to the ability to plan and deliver treatments with greater conformality, sparing normal tissue and organs at risk. Radiotherapy treatment plans aim to meet set dosimetric constraints, and meet them at every fraction. Plan robustness is a measure of deviation between the delivered dose distribution and the planned dose distribution. Due to the same characteristics that make protons advantageous, conventional means of using margins to create a Planning Target Volume (PTV) to ensure plan robustness are inadequate. Additional to this, without a PTV, a new method of analysing plan quality is required in proton therapy. My original contribution to the knowledge in this area is the demonstration of how site- and centre- specific robustness constraints can be established. Robustness constraints can be used both for proton plan analysis and to identify patients that require plans of greater individualisation. I have also used the daily volumetric imaging from patients previously treated with conventional radiotherapy to quantify range uncertainty from inter- and intra-fraction motion. These new methods of both quantifying and analysing the change in proton range in the patient can aid in the choice of beam directions, provide input into a multi- criteria optimisation algorithm or can be used as criteria to determine when adaptive planning may be required. This greater understanding in range uncertainty better informs the planner on how best to balance the trade-off between plan conformality and robustness in proton therapy. This research is directly relevant to furthering the knowledge base in light of HM Government pledging £250 million to build two proton centres in England, to treat NHS patients from 2018. Use of methods described in this dissertation will aid in the establishment of clear and pre-defined protocols for treating patients in the future.
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Neal, Anthony James. "Optimisation of radiotherapy treatment planning for tumours of the breast, prostate and brain." Thesis, King's College London (University of London), 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.306922.
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Bin-Ibrahim, Ahmad Asrul. "Operational planning and optimisation in active distribution systems for flexible and resilient power." Thesis, Durham University, 2018. http://etheses.dur.ac.uk/12872/.
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The electricity network is undergoing significant changes to cater to environmental-deterioration and fuel-depletion issues. Consequently, an increasing number of renewable resources in the form of distributed generation (DG) are being integrated into medium-voltage distribution networks. The DG integration has created several technical and economic challenges for distribution network operators. The main challenge is basically the problem of managing network voltage profile and congestion which is caused by increasing demand and intermittent DG operations. The result of all of these changes is a paradigm shift in the way distribution networks operate (from passive to active) and are managed that is not limited only to the distribution network operator but actively engages with network users such as demand aggregators, DG owners, and transmission-system operators. This thesis expands knowledge on the active distribution system in three specific areas and attempts to fill the gaps in existing approaches. A comprehensive active network management framework in active distribution systems is developed to allow studies on (i) the flexibility of network topology using modern power flow controllers, (ii) the benefits of centralised thermal electricity storage in achieving the required levels of flexibility and resiliency in an active distribution system, and (iii) system resiliency toward fault occurrence in hybrid AC/DC distribution systems. These works are implemented within the Advanced Interactive Multidimensional Modelling Systems (AIMMS) software to carry out optimisation procedure. Results demonstrate the benefit provided by a range of active distribution system solutions and can guide future distribution-system operators in making practical decisions to operate active distribution systems in cost-effective ways.
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Laptali, Emel. "Application of optimisation techniques to planning and estimating decisions in the building process." Thesis, University of South Wales, 1996. https://pure.southwales.ac.uk/en/studentthesis/application-of-optimisation-techniques-to-planning-and-estimating-decisions-in-the-building-process(3bc5337e-375b-43b8-acd9-3dc12553eb61).html.
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An integrated computer model for time and cost optimisation has been developed for multi-storey reinforced concrete office buildings. The development of the model has been based on interviews completed with Planners, Estimators and Researchers within 2 of the top 20 (in terms of turnover) UK main contractors, and on published literature, bar charts and bills of quantities of concrete framed commercial buildings. The duration and cost of construction of a typical multistorey reinforced concrete office building is calculated through the first part of the integrated model, i.e. the simulation model. The model provides a set of choices for the selection of materials and plant and possible methods of work. It also requires the user to input the quantities of work, gang sizes and the quantity of plant required, lag values between activities, output rates, unit costs of plant, labour costs and indirect costs. A linked bar chart is drawn automatically by using the data available from the simulation model. The second part of the model, (optimisation) uses the data provided by the simulation part and provides sets of solutions of time vs. cost from which the minimum project cost corresponding to the optimum project duration is calculated under the given schedule restrictions. Linear programming is used for the optimisation problem. The objective function is set to be the minimisation of the project cost which is the total of the direct costs of all the activities creating the project and the indirect costs of the project. The constraints are formulated from the precedence relationship, lag values, and normal and crash values of time and cost for the activities supplied by the simulation model. The simulation part has been validated by comparing and contrasting the results with those methods and practices adopted by commercial planners and estimators. The validation of the optimisation part has been undertaken by plotting time-direct cost curves from the results and checking the convexity of the curves. Additionally, the validation procedures included taking account of the opinions of practitioners in the industry on the practical and commercial viability of the model.
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Steffansson, Hlynur. "Methods and algorithms for integrated multi-scale optimisation of production planning and scheduling." Thesis, Imperial College London, 2007. http://hdl.handle.net/10044/1/7437.
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Delolme, Laurent. "Optimisation multicritères de gammes d'usinages." Thesis, Université Clermont Auvergne (2017-2020), 2017. http://www.theses.fr/2017CLFAC019.
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L’objectif de ces travaux est de développer une méthodologie de génération automatique de gammes d’usinage optimises et innovantes qui permettent aux sous-traitants aéronautiques de faire face aux problématiques de productivité et de compétitivité actuelles. Dans un premier temps, un état de l’art sur les systèmes existants de génération de gammes est présenté et permet d’introduire les limites des systèmes actuels. Une méthodologie en quatre étapes est ensuite proposée, permettant à l’utilisateur d’obtenir des gammes d’usinage optimisées respectant son savoir-faire et son expérience et introduisant de l’innovation. Cette méthodologie s’appuie sur une représentation du comportement décisionnel des méthodistes dans une situation donnée ainsi que face au risque à l’industrialisation et élargit la formalisation de la performance d’une gamme en prenant en compte d’autres critères de performance autres que le temps d’usinage ou le coût global. Ainsi, un état de l’art sur les méthodes d’aide à la décision multicritère permet de sélectionner la méthode pour l’agrégation des performances par rapport à la problématique industrielle. Après une description géométrique et technologique de la pièce et la création par les méthodistes, d’opérations d’usinage élémentaires, un algorithme génétique est utilisé pour générer des gammes optimisées. Lors d’une dernière étape, la méthodologie présente les meilleures gammes générées au méthodiste et l’utilisation de la théorie du choix social lui permet de cibler les gammes les plus performantes à implanter, en intégrant un critère de risque à l’industrialisation. Cette méthodologie a été appliquée à une pièce de train d’atterrissage usinée en alliage de Titane et a permis une diminution de 25% du temps d’usinage tout en augmentant la fiabilisation. Des perspectives d’amélioration de l’outil d’aide à la décision, à diverses étapes de la méthodologie, sont enfin proposées<br>The objective of this work is to develop a Computer-Aided Process Planning (CAPP) methodology to allow aeronautical subcontractors to face the current productivity and competitiveness problems. To start, a state of the art on the existing CAPP systems is presented and introduce the limits of the current systems. A four-step methodology is then proposed, allowing the user to obtain optimized machining ranges respecting his know-how and experience and introducing innovation. This methodology is based on a representation of the decision-making behavior of the process planners in a given situation as well as the risk of industrialization and broadens the formalization of the performance by taking into account performance criteria other than the machining time or cost. Thus, a state of the art on multicriteria decision-making methods helps to select the method for the aggregation of performance in relation to the industrial problem. After a geometrical and technological description of a mechanical part and the creation by the process planners of elementary machining operations, a genetic algorithm is used to generate optimized ranges. In a final step, the methodology presents the best process plans generated to the process planners and the use of the social choice theory allows to target the most efficient ones to choose, integrating a risk criterion based on tool deflection. This methodology was applied to a Titanium alloy machined landing gear part and allowed a 25% reduction in machining time while increasing reliability. Finally, prospects for improving the decision-making tool at various stages of the methodology are proposed
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Pongcharoen, Pupong. "Genetic algorithms for production scheduling in capital goods industries." Thesis, University of Newcastle Upon Tyne, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.366573.
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Li, Yuan. "Studies on collaborative transportation planning among carriers." Thesis, Troyes, 2017. http://www.theses.fr/2017TROY0008/document.
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Dans la collaboration entre transporteurs, plusieurs transporteurs forment une alliance pour échanger leurs demandes de transport dans le but d'améliorer la rentabilité. Dans cette thèse, nous avons étudié la planification collaborative de transport entre transporteurs de charges partielles. Plus concrètement, nous avons étudié trois sous-problèmes soulevés dans cette planification collaborative: le problème de ramassage et de livraison avec fenêtres de temps, profits et demandes réservées, le problème de détermination de gagnants dans l'échange combinatoire, et le problème de génération d'enchère.Ces trois sous-problèmes sont les problèmes clés pour la planification collaborative de transport parmi des transporteurs, et ils sont peu étudiés dans la littérature. Nous avons établi les nouveaux modèles de programmation mathématique pour ces problèmes et développé des heuristiques efficaces pour trouver des solutions très proches de leurs optimums dans un temps de calcul raisonnable. Les heuristiques proposées sont plus performantes que les solveurs commerciaux (GUROBI, CPLEX) non seulement en termes de la qualité de solution, mais aussi en termes du temps de calcul<br>In carrier collaboration, multiple carriers form an alliance to exchange their delivery requests for the purpose of improving profitability. In this thesis, we have studied the collaborative transportation planning (CTP) among less-than-truckload (LTL) carriers. More concretely, we have studied three sub-problems raised in this collaborative planning: the pickup and delivery problem with time windows, profits, and reserved requests (PDPTWPR), the winner determination problem (WDP) in carrier collaboration via combinatorial exchange (CE), and the bid generation problem (BGP).These sub-problems are the key issues for collaborative transportation planning among carriers, and they are rarely studied in the literature. We have established new mathematical programming models for these problems and developed efficient heuristics to find solutions close to their optimums in a reasonable computational time. The heuristics proposed are more efficient than commercial solvers (GUROBI, CPLEX) not only in terms of solution quality, but also in terms of computation time
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Grebenkin, Ivan Mikhailovich. "A new optimisation procedure for uncertainty reduction by intelligent wells during field development planning." Thesis, Heriot-Watt University, 2013. http://hdl.handle.net/10399/2704.
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The uncertainty in the produced oil volume can be minimised by substituting intelligent wells (IWs) for conventional wells. A previous study showed that IWs reduce the impact of geological uncertainty on the production forecast (Birchenko, Demyanov et al. 2008). This investigation has now been extended to the “dynamic” parameters (fluid contacts, relative permeabilities, aquifer strength and zonal skin). The efficiency of the IWs in reducing the total production uncertainty due to the reservoir’s dynamic parameters was found to be comparable to that reported for the static parameters. However, this later study identified that the result was strongly dependent on the strategy employed to optimise the field’s performance. Experience has shown that challenges arise while using commercial software for optimisation of a typical, modern field with multiple reservoirs and a complex surface production network. Inclusion of the optimisation algorithm dramatically increases the calculation time in addition to showing stability and convergence problems. This thesis describes the development of a novel method of a reactive control strategy for ICVs that is both robust and computationally fast. The developed method identifies the critical water cut threshold at which a well will operate optimally when on/off valves are used. This method is not affected by the convergence problems which have lead to many of the difficulties associated with previous efforts to solve our non-linear optimisation problem. Run times similar to the (non-optimised) base case are now potentially possible and, equally importantly, the optimal value calculated is similar to the result from the various optimisation software referred to above. The approach is particularly valuable when analysing the impact of uncertainty on the reservoir’s dynamic and static parameters, the method being convergent and independent of the point used to initiate the optimization process. “Tuning” the algorithm’s optimisation parameters in the middle of the calculation is no longer required; thus ensuring the results from the many realisations are comparable.
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Wruk, Julian [Verfasser]. "An Optimisation Approach to Automated Strategic Network Planning at Low-Voltage Level / Julian Wruk." Berlin : epubli, 2021. http://d-nb.info/1239980744/34.
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Pakzad, Shahabi Maedeh. "Desalination water supply planning – Optimisation of environmental impacts and costs using life cycle assessment." Thesis, Pakzad Shahabi, Maedeh (2015) Desalination water supply planning – Optimisation of environmental impacts and costs using life cycle assessment. PhD thesis, Murdoch University, 2015. https://researchrepository.murdoch.edu.au/id/eprint/29533/.
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Desalination is an integral component of water supply for many cities and regions around the globe. Although, desalination can offer a rainfall independent source of water and provide social benefits, it is energy intensive compared to conventional water sources and can have significant impacts upon the environment. Therefore an interdisciplinary approach is required when planning for water supply by desalination. A life cycle assessment of a desalination supply chain can be integrated into an optimisation framework to simultaneously consider all possible planning alternatives and find the combination of planning decisions that optimizes environmental and economic objectives. This thesis aimed to develop a desalination supply chain optimization life cycle framework to analyze the economic and environmental impacts and trade-offs for alternative planning scenarios. The framework used life cycle assessment and a levelised cost model to quantify and compare the supply chain environmental and economic impacts for a range of planning scenarios. The framework incorporated a mixed integer linear programming model to determine optimal planning decisions such as water capacity expansion of each type of desalination technology over a planning horizon, and optimal locations of new desalination plants while considering interdependencies among water distribution and treatment processes. The framework was tested for future seawater reverse osmosis desalination planning in the northern metropolitan area of Perth, Western Australia over the next 20 years.
Results indicated that, a decentralised desalination supply system with small and medium-sized SWRO plants integrated into the Perth metropolitan area could achieve a lower environmental and economic impact, when compared to a centralised supply system with a large desalination plant located far from final demand. Improving seawater quality by introducing beach well intake - a mature intake technology for smaller-sized plants - could further promote the decentralised supply system environmental and economic performance. The capital expenditure contribution to total cost for the treatment facilities in the decentralised supply system was found to be higher than for the centralised supply system. However, this was outweighed by the significant water distribution pipeline construction and operational expenditure savings and also the operational expenditure savings associated with lower chemical and electricity use in the beach well plants. Construction phase contribution to treatment facilities life cycle environmental impact for the decentralised supply system was found to be higher than for the centralised supply system due to diseconomy of scale in smaller-sized plants. However, this was outweighed by significant water distribution pipeline construction and operational environmental impacts savings. Smaller plants with beach well intake benefit from operational environmental impact savings associated with lower chemical and electricity use. Multi-staged construction of successive small plants compared to single-stage construction of a large plant provided better economic outcomes due to lower interest costs. However, multi-staged construction led to higher environmental impacts associated with diseconomy of scale in the plant construction phase.
The case study provided numerous insights that were only possible through the use of a life-cycle optimization framework. For example, in desalination planning for a metropolitan area with land scarcity for siting new plants, the factors of supply system configuration, land-use patterns, environmental impacts and economic costs are highly inter-related and decision makers can consider these as a whole rather than considering each separately. The transparency and flexibility of the framework allows professionals from different disciplines to test the scenarios in a quantitative manner, to understand potential planning implications.
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Capitanul, Elena Mihaela. "Airport strategic planning under uncertainty : fuzzy dual dynamic programming approach." Thesis, Toulouse 3, 2016. http://www.theses.fr/2016TOU30109/document.
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Les aéroports sont des connecteurs critiques dans le système opérationnel de transport aérien. Afin de répondre à leurs obligations opérationnelles, économiques et sociales dans un environnement très volatil, ont besoin d'aéroports à embrasser le changement plutôt que d'y résister. Comme toute autre industrie, font face à des aéroports un large éventail de risques, dont certains spécifiques au transport aérien, les autres ayant seulement une influence indirecte mais assez puissant pour perturber les activités aéroportuaires. La planification longue terme de l'aéroport est devenue une question complexe en raison de la croissance constante de la demande de trafic aérien. Une nouvelle dimension de complexité est apparue lorsque l'incertitude a commencé à avoir un impact plus en plus perturbatrice, et significativement coûteuse sur le développement des infrastructures aéroportuaires. Historiquement, la capacité des outils traditionnels pour atténuer le risque et l'incertitude ont avérée inefficace. D'innombrables événements imprévus comme les attaques terroristes, la récession économique, les catastrophes naturelles, ont eu un impact dramatique sur les niveaux de trafic, certains avec une portée mondiale. Pour ce type hautement improbable d'événements peut être ajouté les progrès technologiques, de nouvelles modèles d'affaires des compagnies aériennes et aéroports, les changements de politique et de réglementation, préoccupation croissante pour l'impact environnemental. Dans ce contexte, la thèse met en avant une approche novatrice pour aborder l'évaluation des risques et de l'atténuation dans l'incertitude dans les projets de développement des infrastructures aéroportuaires à long terme. La thèse se développe sur le formalisme récemment développée de nombres flous comme un outil clé pour aborder l'incertitude. Après un examen approfondi de l'industrie aéroportuaire dans le contexte des environnements incertains, nombres double flous et double floue arithmétiques sont introduits. Comme le projet de développement des infrastructures aéroportuaires est un autre cas de problème de prise de décision en plusieurs étapes, la programmation dynamique est prise en compte afin d'optimiser le processus séquentiel de prise de décision. L'originalité de l'approche réside dans le fait que l'ensemble du processus sera floue et la composante double floue de la programmation dynamique sera introduite. Pour valider notre méthode, une étude de cas sera développée<br>Airports are critical connectors in the air transportation operational system. In order to meet their operational, economic and social obligations in a very volatile environment, airports need to embrace change rather than resist it. Like any other industry, airports face a wide array of risks, some specific to air transportation, other having only an indirect influence but powerful enough to disrupt airport activities. Long term airport planning has become a complex issue due to the constant growth in air traffic demand. A new dimension of complexity emerged when uncertainty began having a more, and more disruptive, and significantly costly impact on developing airport infrastructure. Historically, the ability of traditional risk and uncertainty mitigation tools proved inefficient. Countless unforeseen events like terrorist attacks, economic recession, natural disasters, had a dramatic impact on traffic levels, some with a global reach. To these highly improbable type of events can be added technological advancements, new airlines and airports business models, policy and regulation changes, increasing concern for environmental impact. In this context, the thesis puts forward an innovative approach for addressing risk assessment and mitigation under uncertainty in long-term airport infrastructure development projects. The thesis expands on the newly developed formalism of fuzzy dual numbers as a key tool to address uncertainty. After a comprehensive review of the airport industry in the context of uncertain environments, fuzzy dual numbers and fuzzy dual calculus are introduced. Since airport infrastructure development project is another case of multi-stage decision-making problem, dynamic programming is considered in order to optimize the sequential decision making process. The originality of the approach resides in the fact that the entire process will be fuzzified and fuzzy dual dynamic programming components will be introduced. To validate our method, a study case will be developed