Search Techniques for Multi-Objective Optimization of Mixed-Variable Systems Having Stochastic Responses

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/13168 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/13168 http://eprints.org/relation/isCoversheetVersionOf https://pure.iiasa.ac.at/id/document/13168 archive 351 disk0/00/00/84/41 2016-01-15 08:40:35 2021-08-27 17:20:13 2016-01-15 08:40:35 monograph show 2 Walston J.G. 8284 Search Techniques for Multi-Objective Optimization of Mixed-Variable Systems Having Stochastic Responses pub iis_mod prog_ime prog_ysp A method is proposed for solving stochastic multi-objective optimization problems. Such problems are typically encountered when one desires to optimize systems with multiple, often competing, objectives that do not have a closed form representation and must be estimated via simulation. A two-stage method is proposed that combines generalized pattern search/ranking and selection (GPS/R&S) and and Mesh Adaptive Direct Search (MADS) developed for single-objective stochastic problems with three multi-objective methods: interactive techniques for the specification of aspiration/reservation levels, scalarization functions, and multi-objective ranking and selection. This combination is devised specifically so as to keep the desirable convergence properties of GPS/R&S and MADS while extending application to the multi-objective case. 2007-05 published IR-07-014 IR-07-014 1651 public interim_report IIASA, Laxenburg, Austria 32 FALSE info:eu-repo/semantics/book