An adaptive learning approach for no-wait flowshop scheduling problems to minimize makespan

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dc.contributor.authorEngin, Orhan
dc.contributor.authorGünaydın, Cengiz
dc.date.accessioned2020-03-26T18:13:43Z
dc.date.available2020-03-26T18:13:43Z
dc.date.issued2011
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractNo-wait flowshop scheduling problem (NW-FSSP) with the objective to minimize the makespan is an important sequencing problem in the production plans and applications of no-wait flowshops can be found in several industries. In a NW-FSSP, jobs are not allowed to wait between two successive machines. The NW-FSSPs are addressed to minimize makespan and the NW-FSSP is known as a NP- Hard problem. In this study, Agarwal et al.'s(1) adaptive learning approach (ALA) is improvement for NW-FSSPs. Improvements in adaptive learning approach is similar to neural-network training. The improvement adaptive learning approach (IALA) is applied to all of the 192 problems. The proposed IALA method for NW-FSSP is compared with Aldowaisan and Allahverdi's(2) results by using Genetic heuristic. The results of computational experiments on randomly generated NW-FSSPs are show that the proposed adaptive learning approach performs quite well.en_US
dc.identifier.endpage529en_US
dc.identifier.issn1875-6883en_US
dc.identifier.issue4en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage521en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12395/26101
dc.identifier.volume4en_US
dc.identifier.wosWOS:000297795000011en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherATLANTIS PRESSen_US
dc.relation.ispartofINTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMSen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectNo-wait flowshopen_US
dc.subjectAdaptive learning approachen_US
dc.subjectGenetic algorithmen_US
dc.subjectMakespanen_US
dc.titleAn adaptive learning approach for no-wait flowshop scheduling problems to minimize makespanen_US
dc.typeArticleen_US

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