Integration of genetic algorithm and Monte Carlo to analyze the effect of routing flexibility

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dc.authoridGOCKEN, Mustafa/0000-0002-1256-2305
dc.authoridFARUK, GEYIK/0000-0001-8732-0629
dc.authoridDosdogru, Ayse Tugba/0000-0002-1548-5237
dc.authoridGeyik, Faruk/0000-0002-2355-0529
dc.contributor.authorDosdogru, Ayse Tugba
dc.contributor.authorGocken, Mustafa
dc.contributor.authorGeyik, Faruk
dc.date.accessioned2025-01-06T17:44:33Z
dc.date.available2025-01-06T17:44:33Z
dc.date.issued2015
dc.description.abstractFlexibility is an important task for effectively utilizing resources in a manufacturing system and responding demands rapidly. In manufacturing systems, there exist different types of flexibility levels. In this study, the stochastic flexible job shop scheduling problem is considered to measure the impact of routing flexibility on shop performance. Thus, an integrated genetic algorithm-Monte Carlo method is proposed to analyze the effect of routing flexibility. To make the problem more realistic, system parameters (processing times, operation sequences, etc.) are generated randomly via Monte Carlo. An experimental design is utilized to analyze main and interaction effects of the factors considered (i.e., number of parts, number of machines, number of operations, and flexibility levels) by using a genetic algorithm which is specifically designed for the stochastic flexible job shop scheduling problem. In developed genetic algorithm, different initial strategies which not only improve solution quality but also decrease solution time are used. Makespan is specified as the objective function to be minimized. Results are analyzed with a full factorial analysis of variance. Comprehensive discussions of results are given case by case.
dc.identifier.doi10.1007/s00170-015-7247-3
dc.identifier.endpage1389
dc.identifier.issn0268-3768
dc.identifier.issn1433-3015
dc.identifier.issue5-8
dc.identifier.scopus2-s2.0-84988216150
dc.identifier.scopusqualityQ1
dc.identifier.startpage1379
dc.identifier.urihttps://doi.org/10.1007/s00170-015-7247-3
dc.identifier.urihttps://hdl.handle.net/20.500.14669/3068
dc.identifier.volume81
dc.identifier.wosWOS:000363718600057
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherSpringer London Ltd
dc.relation.ispartofInternational Journal of Advanced Manufacturing Technology
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241211
dc.subjectStochastic flexible job shop scheduling
dc.subjectRouting flexibility
dc.subjectGenetic algorithm
dc.subjectMonte Carlo simulation
dc.titleIntegration of genetic algorithm and Monte Carlo to analyze the effect of routing flexibility
dc.typeArticle

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