A comparison of combat genetic and big bang-big crunch algorithms for solving the buffer allocation problem

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dc.authoridDemir, Leyla / 0000-0002-9036-6895
dc.authoridKoyuncuoglu, Mehmet Ulas / 0000-0002-5437-1865
dc.authorscopusid57218802423
dc.authorscopusid36809216100
dc.authorwosidDemir, Leyla/F-9125-2011
dc.authorwosidKoyuncuoglu, Mehmet Ulas/H-5629-2018
dc.contributor.authorKoyuncuoğlu, Mehmet Ulaş
dc.contributor.authorDemir, Leyla
dc.date.accessioned2022-02-15T16:58:04Z
dc.date.available2022-02-15T16:58:04Z
dc.date.issued2021
dc.departmentBakırçay Üniversitesien_US
dc.description.abstractThe buffer allocation problem (BAP) aims to determine the optimal buffer configuration for a production line under the predefined constraints. The BAP is an NP-hard combinatorial optimization problem and the solution space exponentially grows as the problem size increases. Therefore, problem specific heuristic or meta-heuristic search algorithms are widely used to solve the BAP. In this study two population-based search algorithms; i.e. Combat Genetic Algorithm (CGA) and Big Bang-Big Crunch (BB-BC) algorithm, are proposed in solving the BAP to maximize the throughput of the line under the total buffer size constraint for unreliable production lines. Performances of the proposed algorithms are tested on existing benchmark problems taken from the literature. The experimental results showed that the proposed BB-BC algorithm yielded better results than the proposed CGA as well as other algorithms reported in the literature.en_US
dc.identifier.doi10.1007/s10845-020-01647-1
dc.identifier.endpage1546en_US
dc.identifier.issn0956-5515
dc.identifier.issn1572-8145
dc.identifier.issue6en_US
dc.identifier.scopus2-s2.0-85091184392en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage1529en_US
dc.identifier.urihttps://doi.org/10.1007/s10845-020-01647-1
dc.identifier.urihttps://hdl.handle.net/20.500.14034/339
dc.identifier.volume32en_US
dc.identifier.wosWOS:000571084100002en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.journalJournal Of Intelligent Manufacturingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBuffer allocation problemen_US
dc.subjectThroughput maximizationen_US
dc.subjectProduction linesen_US
dc.subjectCombat genetic algorithmen_US
dc.subjectBig bang-big crunch algorithmen_US
dc.subjectTabu Search Approachen_US
dc.subjectEvolutionary Algorithmen_US
dc.subjectProduction Linesen_US
dc.subjectStorage Spaceen_US
dc.subjectOptimizationen_US
dc.subjectSystemsen_US
dc.subjectMachinesen_US
dc.subjectDesignen_US
dc.subjectMaintenanceen_US
dc.titleA comparison of combat genetic and big bang-big crunch algorithms for solving the buffer allocation problemen_US
dc.typeArticleen_US

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