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 32 for “"Heuristic optimization"”.
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Advances and applications in high-dimensional heuristic optimization
… real-world decision scenarios, multiobjective optimization is an area of multicriteria decision-making that seeks to simultaneously optimize two or more conflicting objectives. In contrast to single-objective scenarios, nontrivial multiobjective optimization problems are characterized by a set …
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Water resources decision making using meta-heuristic optimization methods
… The dissertation's focus was to investigate meta-heuristic (global) optimization methods suitable for developing water resources decision support system (DSS), particularly to optimally design and operate groundwater storage and recovery projects. The effort included developing an integrated …
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A Capacity Expansion Planning Method for A Regional Water Supply System (Illinois)
The goal of this study is to develop an optimization model for designing an economical regional water supply system which consists of water production and water transmission facilities. Water demands are assumed to be increasing over a planning horizon and to be satisfied from several potential …
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An interleaving warehouse layout model
… cost (order picking cost plus inventory cost). A heuristic optimization technique is developed and applied to a set of realistic, hypothetical problems. This model allows warehouse management to assess the tradeoffs in handling costs among various stock arrangements and reorder quantities to …
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Métodos iterativos de análise hidráulica e dimensionamento ótimo por programação linear de redes de distribuição de água
… a nodal formulation is used into an economical optimization of water distribution networks, which is only based on heuristic percepts. The outcomes of this heuristic optimization are compared to those obtained through an linear optimization model. This model uses linear programming together with …
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Towards Ethical Machine Learning: New Algorithms For Fairness And Privacy
… hard accuracy constraint? • How can we leverage heuristic optimization oracles for private learning while still maintaining rigorous privacy guarantees? • How can we extend the coarse fairness protections provided by statistical notions of fairness to richer subgroup classes? • How can we learn …
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QoS and trust prediction framework for composed distributed systems
… set of services to create composed systems using heuristic optimization algorithms. Additionally, the prediction model is used at runtime with fast heuristic techniques to build adaptable composed systems. The empirical results show the proposed context-dependent framework performs well in …
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Magnetocardiography in unshielded environment based on optical magnetometry and adaptive noise cancellation
… Least-Mean-Squares (LMS) algorithms and on two heuristic optimization techniques, namely, Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). The use of these algorithms is investigated for suppressing the power line generated 50Hz interference and recovering of the weak magnetic …
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Cognitive UAS Path-Planning for Large Spatial Search
… a pseudo-random search method, known as meta-heuristics, is used to develop a new path planning algorithm to search the field in an intelligent manner. This work develops a means of turning meta-heuristic optimization into a cognitive navigation with autonomous path-planning algorithm that is …
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Buffer optimization and robust design studies in asynchronous assembly systems using design of experiments approach
… Furthermore, the use of DoE approach as an optimization tool is proposed, principally in cases where little known on the AAS that will be designed. Case studies using the DoE approach as a heuristic optimization method are presented. Additionally, in an attempt to study its effect, in some …
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Simplifying multiple-statement reductions with the polyhedral model
… reduction problem as a bilinear optimization problem. We present a heuristic optimization algorithm for these reductions, and we demonstrate that the algorithm provides optimal complexity for a set of benchmark programs from the literature on probabilistic inference algorithms, …
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Optimizing Quantum Circuit Layout using Quantum Annealing
… technique and use Quantum Annealing in the optimization part. The first approach optimizes a quantum circuit by global qubit line reordering based on the Graph Partitioning problem formulation. The second approach implements local qubit line reordering using Boolean satisfiability theory. As …
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Simulated Response of Degrading Hysteretic Joints With Slack Behavior
… accounts for material property variation; and a heuristic optimization routine estimates the parameters needed. The core model is a modified array of differential equations whose solution describes accurate hysteresis shapes for slack systems. Hysteresis parameter identification is carried out by …
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Inverse Design and Optimization Methods for Thermophotovoltaic Emitters made of Tungsten Gratings
… is infeasible. This prompts the use of metaheuristics. It should be noted that due to the stochastic nature of these optimization methods, a globally optimal solution is not guaranteed, and instead, these methods seek to provide "close enough" solutions. Generally, metaheuristic algorithms …
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Prediction of Enrollment using Computational Intelligence
… prediction. A variation of population based heuristic optimization approach, namely, co-operative particle swarm optimization (COPSO), has been used to estimate the parameters for the SMN, the combination is termed here as COPSO-SMN. The second CI technique used for time series prediction is …
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A novel automated approach of multi-modality retinal image registration and fusion
… control points. The second contribution is the heuristic optimization algorithm that maximizes Mutual-Pixel-Count (MPC) objective function. The initially selected control points are adjusted during the optimization at the sub-pixel level. A global maxima equivalent result is achieved by …
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Improvement of Work Process Performance with Task Assignments and Mental Workload Balancing
… instantaneous workload, a utilized simulation-optimization approach solves this problem. More specifically, a discrete event human performance simulation model evaluates the objective function of the problem coupled with a genetic algorithm based meta-heuristic optimization approach to search …
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Auto-Scaling Containerized Microservice Applications
… when appropriate. I develop MOAT, a novel heuristic optimization technique that ensures that the pre-computed allocations satisfy response time targets efficiently. Using a variety of analytical, on-premise, and public cloud systems, I show that MOAT and TRIM outperform state-of-the-art …
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Burstiness and Uncertainty Aware Service Level Planning for Enterprise Clouds
… applications to satisfy their bursts. RAP is a heuristic optimization technique that in conjunction with a trace-driven performance prediction technique estimates the near minimal degree of service level violations that the cloud SP can incur with a given cloud resource capacity. RAP works in …
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