Multicriteria inventory classification using a genetic algorithm

dc.citation.epage37en_US
dc.citation.issueNumber1en_US
dc.citation.spage29en_US
dc.citation.volumeNumber105en_US
dc.contributor.authorGuvenir, H. A.en_US
dc.contributor.authorErel, E.en_US
dc.date.accessioned2016-02-08T10:45:45Z
dc.date.available2016-02-08T10:45:45Zen_US
dc.date.issued1998en_US
dc.departmentDepartment of Computer Engineeringen_US
dc.departmentDepartment of Managementen_US
dc.description.abstractOne of the application areas of genetic algorithms is parameter optimization. This paper addresses the problem of optimizing a set of parameters that represent the weights of criteria, where the sum of all weights is 1. A chromosome represents the values of the weights, possibly along with some cut-off points. A new crossover operation, called continuous uniform crossover, is proposed, such that it produces valid chromosomes given that the parent chromosomes are valid. The new crossover technique is applied to the problem of multicriteria inventory classification. The results are compared with the classical inventory classification technique using the Analytical Hierarchy Process. © 1998 Elsevier Science B.V.en_US
dc.identifier.doi10.1016/S0377-2217(97)00039-8en_US
dc.identifier.eissn1872-6860
dc.identifier.issn0377-2217
dc.identifier.urihttp://hdl.handle.net/11693/25497en_US
dc.language.isoEnglishen_US
dc.publisherElsevieren_US
dc.relation.isversionofhttps://doi.org/10.1016/S0377-2217(97)00039-8en_US
dc.source.titleEuropean Journal of Operational Researchen_US
dc.subjectAnalytical Hierarchy Processen_US
dc.subjectComputersen_US
dc.subjectGenetic Algorithmsen_US
dc.subjectInventoryen_US
dc.subjectMulti-Criteria Analysisen_US
dc.subjectComputersen_US
dc.subjectGenetic Algorithmsen_US
dc.subjectHierarchical Systemsen_US
dc.subjectOptimizationen_US
dc.subjectInventoryen_US
dc.subjectMulti-Criteria Analysisen_US
dc.subjectOperations Researchen_US
dc.titleMulticriteria inventory classification using a genetic algorithmen_US
dc.typeArticleen_US

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