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Search Techniques For Multi-Objective Optimization Of Mixed Variable Systems Having Stochastic Responses, Jennifer G. Walston
Search Techniques For Multi-Objective Optimization Of Mixed Variable Systems Having Stochastic Responses, Jennifer G. Walston
Theses and Dissertations
A research approach is presented for solving stochastic, multi-objective optimization problems. First, the class of mesh adaptive direct search (MADS) algorithms for nonlinearly constrained optimization is extended to mixed variable problems. The resulting algorithm, MV-MADS, is then extended to stochastic problems (MVMADS-RS), via a ranking and selection procedure. Finally, a two-stage method is developed that combines the generalized pattern search/ranking and selection (MGPS-RS) algorithms for single-objective, mixed variable, stochastic problems with a multi-objective approach that makes use of interactive techniques for the specification of aspiration and reservation levels, scalarization functions, and multi-objective ranking and selection. A convergence analysis for the …
Critical Infrastructure Rebuild Prioritization Using Simulation Optimization, Namsuk Cho
Critical Infrastructure Rebuild Prioritization Using Simulation Optimization, Namsuk Cho
Theses and Dissertations
This thesis examines the importance of a critical infrastructure rebuild strategy following a terrorist attack or natural disaster such as Hurricane Katrina. Critical infrastructures are very complex and dependent systems in which their re-establishment is an essential part of the rebuilding process. A rebuild simulation model consisting of three layers (physical, information, and spatial) captures the dependency between the six critical infrastructures modeled. We employ a simulation optimization approach to evaluate rebuild prioritization combinations with a goal of minimizing the time needed to achieve an acceptable rebuild level. We use a simulated annealing heuristic as an optimization technique that works …
Prioritizing Satellite Payload Selection Via Optimization, Benjamin S. Kallemyn
Prioritizing Satellite Payload Selection Via Optimization, Benjamin S. Kallemyn
Theses and Dissertations
This thesis develops optimization models for prioritizing payloads for inclusion on satellite buses with volume, power, weight and budget constraints. The first model considers a single satellite launch for which the budget is uncertain and constellation requirements are not considered. Subsequently, we include constellation requirements and provide a more enhanced model. Both single-launch models provide a prioritized list of payloads to include on the launch before the budget is realized. The single-launch models are subsequently extended to a sequence of multiple launches in two cases, both of which incorporate an explicit dependence on the constellation composition at each launch epoch. …