A problem space genetic algorithm in multiobjective optimization

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dc.citation.epage378en_US
dc.citation.issueNumber3-4en_US
dc.citation.spage363en_US
dc.citation.volumeNumber14en_US
dc.contributor.authorTürkcan, A.en_US
dc.contributor.authorAktürk, M. S.en_US
dc.date.accessioned2016-02-08T10:29:59Z
dc.date.available2016-02-08T10:29:59Z
dc.date.issued2003en_US
dc.departmentDepartment of Industrial Engineeringen_US
dc.description.abstractIn this study, a problem space genetic algorithm (PSGA) is used to solve bicriteria tool management and scheduling problems simultaneously in flexible manufacturing systems. The PSGA is used to generate approximately efficient solutions minimizing both the manufacturing cost and total weighted tardiness. This is the first implementation of PSGA to solve a multiobjective optimization problem (MOP). In multiobjective search, the key issues are guiding the search towards the global Pareto-optimal set and maintaining diversity. A new fitness assignment method, which is used in PSGA, is proposed to find a well-diversified, uniformly distributed set of solutions that are close to the global Pareto set. The proposed fitness assignment method is a combination of a nondominated sorting based method which is most commonly used in multiobjective optimization literature and aggregation of objectives method which is popular in the operations research literature. The quality of the Pareto-optimal set is evaluated by using the performance measures developed for multiobjective optimization problems.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T10:29:59Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2003en
dc.identifier.doi10.1023/A:1024605927329en_US
dc.identifier.eissn1572-8145
dc.identifier.issn0956-5515
dc.identifier.urihttp://hdl.handle.net/11693/24477
dc.language.isoEnglishen_US
dc.publisherSpringer New York LLCen_US
dc.relation.isversionofhttp://dx.doi.org/10.1023/A:1024605927329en_US
dc.source.titleJournal of Intelligent Manufacturingen_US
dc.subjectBicriteria schedulingen_US
dc.subjectFlexible manufacturing systemsen_US
dc.subjectGenetic algorithmen_US
dc.subjectLocal searchen_US
dc.subjectNonidentical parallel CNC machinesen_US
dc.subjectPareto-optimalityen_US
dc.subjectApproximation theoryen_US
dc.subjectGenetic algorithmsen_US
dc.subjectProblem solvingen_US
dc.subjectSchedulingen_US
dc.subjectMultiobjective optimizationen_US
dc.subjectFlexible manufacturing systemsen_US
dc.titleA problem space genetic algorithm in multiobjective optimizationen_US
dc.typeArticleen_US

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