Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 21 for “"Multi-objective problems"”.
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Nonconvex optimization algorithm with a new Bi-criteria selection of potential simplices using an estimate of Lipschitz constant /
… RECTangles) type algorithms based on Lipschitz objective function models with unknown Lipschitz constant, which are often applied for practical black-box optimization problems, are considered. The main goal of this thesis is set - to propose a global optimization algorithm for Lipschitz …
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Neiškiliojo optimizavimo algoritmas su nauju bikriteriniu potencialiųjų simpleksų išrinkimu naudojant Lipšico konstantos įvertį /
… RECTangles) type algorithms based on Lipschitz objective function models with unknown Lipschitz constant, which are often applied for practical black-box optimization problems, are considered. The main goal of this thesis is set - to propose a global optimization algorithm for Lipschitz …
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Two Combinatorial Optimization Problems at the Interface of Computer Science and Operations Research
… and heuristic methods are presented. Different multi-objective problems with various numbers of objectives and constraints are used to compare the performances of the proposed algorithms and heuristics.
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The use of prospect theory framework in constrained multi-objective particle swarm optimisation
Many practical problems in the real world nowadays can be formulated as constraintsingle or multiple objective optimisation problems with constraints. Particle swarmoptimisation (PSO) is a population-based stochastic algorithm has been shown to be aneffective optimisation method for solving these …
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Multi-objective cultural algorithms
… approaches are frequently used to solve problems that are not tractable for traditional approaches. Previously, research in the field of evolutionary optimization has focused on single-objective problems. On the contrary, most real-world problems involve more than one objective where …
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A Scalability Study and New Algorithms for Large-Scale Many-Objective Optimization
Many real-world optimization problems contain multiple (often conflicting) goals to be optimized concurrently, commonly referred to as multi-objective problems (MOPs). Over the past few decades, a plethora of multi-objective algorithms have been proposed, often tested on MOPs possessing two or …
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Multi-objective evolutionary optimization in time-changing environments
… techniques for the solution of time-changing multi-objective problems. Many optimization problems, ranging from the design of controllers for time-variant systems to the optimal asset allocation in financial portfolios, need to satisfy multiple conflicting objectives that change in time. Since …
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Reconfigurable satellite constellations for geo-spatially adaptive Earth observation missions
… and optimization of ReCon in low Earth orbits. A multidisciplinary simulation model is developed, to which optimization techniques are applied for both single-objective and multi-objective problems. In addition to the optimized baseline ReCon design, its variants are also considered as case …
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Accelerating MOEA Non-dominated Sorting by Preserving Archival Relationships
… sorting is an important part of many multi-objective evolutionary algorithms (MOEAs). It is used to determine which individuals to keep in the archive of best individuals between generations and to evaluate fitness for breeding. Because this sorting is performed after every generation, …
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Decomposition Evolutionary Algorithms for Noisy Multiobjective Optimization
Multi-objective problems are a category of optimization problem that contain more than one objective function and these objective functions must be optimized simultaneously. Should the objective functions be conflicting, then a set of solutions instead of a single solution is required. This set is …
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Surrogate-based global optimization of composite material parts under dynamic loading
… nonlinear models that are unable to capture multi-body contact. Furthermore, approaches that consider composite failure still remain scarce. This work presents an optimization approach based on design and analysis of computer experiments (DACE) in which smart sampling and continuous metamodel …
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Ant Colony Optimisation for Dynamic and Dynamic Multi-objective Railway Rescheduling Problems
… rescheduling research concentrates on static problems where all delays are known about in advance. However, due to the unpredictable nature of the railway system, it is possible that further unforeseen incidents could occur while the trains are running to the new rescheduled timetable. This …
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A multi-objective evolutionary approach to simulation-based optimisation of real-world problems.
… algorithm described in this thesis integrates multi-objective optimisation, parallelism, surrogate usage, and noise handling in a unique way for dealing with simulation-based optimisation problems incurred by these characteristics. In order to handle multiple, conflicting optimisation …
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Development of Construction Projects Scheduling with Evolutionary Algorithms
… (EAs) as appropriate tools to optimize multi-objective problems have been applied to optimize construction projects in the last two decades. However, studies on improving the convergence ratio and processing time in the most applied algorithms such as Genetic Algorithm (GA), Particle …
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Toward enhancement of evolutionary multi- and many-objective optimization: algorithms, performance metrics, and visualization techniques
In the last three decades, the focus of multi-criteria optimization has been solving problems containing two or three objectives. However, real-world problems generally involve multiple stakeholders and functionalities requiring relatively large number of objectives and decision variables to model …
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In-core Optimization of Pressurised Water Reactor Reload Design via Multi-objective Tabu Search
… assessed one such method’s ability to optimize multiple objectives simultaneously – multi-objective Tabu Search. It was statistically analysed in comparison to other common leading methods – notably the Genetic Algorithm. It was tested on real reactor models using realistic data provided by a …
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Percolation in Two-Dimensional Grain Boundary Structures and Polycrystal Property Closures
… efficient method for finding the closure of a bi-objective optimization problem involving two material properties is formulated. The method is based upon two algorithms developed to find the Pareto front in multi-objective problems — the weighted sum, and the normal boundary intersection methods. …
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Multi-facts devices installation for loss minimization and techno-economic impact assessment using EPSO approach
… technique for optimal location and sizing of multi-unit Flexible Alternating Currents System (FACTS) device installation using single- and multi-objective problems. It also considers techno-economic impact in the system. In this research, the first objective is to develop heuristic technique …
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Racionalización de la red de autobuses de tránsito rápido (BRT): análisis de diferentes objetivos : aplicación a la ciudad de México
… procedimiento búsqueda tabú y procedimiento multiarranque (combina algoritmo constructivo con procedimiento de búsqueda tabú (MultiStartTabu)). Se creó un método específico para este problema, siguiendo la estrategia MOAMP para problemas multiobjetivo. Se compararon los resultados obtenidos …
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Multi-domain multi-objective optimization of mechanisms: a general method with two case studies
… in a loss of optimality when the entire multi-domain system is considered. This thesis presents a general method by which a mechanism optimization problem may be efficiently formulated and solved, considering multiple competing design objectives across multiple analysis domains. Two case …
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