Robust Design using Pareto type optimization: A genetic algorithm with arithmetic crossover

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dc.authorid0000-0002-8291-1419
dc.contributor.authorKoksoy, Onur
dc.contributor.authorYalcinoz, Tankut
dc.date.accessioned2019-08-01T13:38:39Z
dc.date.available2019-08-01T13:38:39Z
dc.date.issued2008
dc.departmentNiğde ÖHÜ
dc.description.abstractIn dual response systems (DRSs) optimization restrictions on the secondary response may rule out better conditions, since an acceptable value for the secondary response is usually unknown. In fact, process conditions that result in a smaller standard deviation are often preferable. Recently, several authors stated that the standard deviation of any performance property could be treated as a new property in its own right as far as Pareto optimizer was concerned. By doing this, there will be many alternative solutions (i.e., the trade-offs between the mean and standard deviation responses) of the DRS problem and Pareto optimization can explore them all. Such analysis is useful, and that is required in order to achieve an improved understanding of the problem before searching for a final optimal solution. In this paper, we again follow this new philosophy and solve the DRS problem by using a genetic algorithm with arithmetic crossover. The genetic algorithm is applied to the printing process problem for improving the quality of a printing process. Genetic algorithms, in contrast to the one-solution-at-a-time approach of most optimization algorithms, maintain a population of hundreds, or thousands, of solutions in speedy manner. (C) 2007 Elsevier Ltd. All rights reserved.
dc.identifier.doi10.1016/j.cie.2007.11.019
dc.identifier.endpage218
dc.identifier.issn0360-8352
dc.identifier.issue1
dc.identifier.scopus2-s2.0-44649105063
dc.identifier.scopusqualityQ1
dc.identifier.startpage208
dc.identifier.urihttps://dx.doi.org/10.1016/j.cie.2007.11.019
dc.identifier.urihttps://hdl.handle.net/11480/5212
dc.identifier.volume55
dc.identifier.wosWOS:000257535700014
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthor[0-Belirlenecek]
dc.language.isoen
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD
dc.relation.ispartofCOMPUTERS & INDUSTRIAL ENGINEERING
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectRobust Design
dc.subjectPareto optimization
dc.subjectquality improvement
dc.subjectgenetic algorithms
dc.titleRobust Design using Pareto type optimization: A genetic algorithm with arithmetic crossover
dc.typeArticle

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