Using ant colony optimization to solve hybrid flow shop scheduling problems

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dc.contributor.authorAlaykıran, Kemal
dc.contributor.authorEngin, Orhan
dc.contributor.authorDöyen, Alper
dc.date.accessioned2020-03-26T17:18:45Z
dc.date.available2020-03-26T17:18:45Z
dc.date.issued2007
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractIn recent years, most researchers have focused on methods which mimic natural processes in problem solving. These methods are most commonly termed "nature-inspired" methods. Ant colony optimization (ACO) is a new and encouraging group of these algorithms. The ant system (AS) is the first algorithm of ACO. In this study, an improved ACO method is used to solve hybrid flow shop (HFS) problems. The n-job and k-stage HFS problem is one of the general production scheduling problems. HFS problems are NP-hard when the objective is to minimize the makespan [1]. This research deals with the criterion of makespan minimization for HFS scheduling problems. The operating parameters of AS have an important role on the quality of the solution. In order to achieve better results, a parameter optimization study is conducted in this paper. The improved ACO method is tested with benchmark problems. The test problems are the same as those used by Carlier and Neron (RAIRO-RO 34(1):1-25, 2000), Neron et al. (Omega 29(6):501-511, 2001), and Engin and Doyen (Future Gener Comput Syst 20(6):1083-1095, 2004). At the end of this study, there will be a comparison of the performance of the proposed method presented in this paper and the branch and bound (B&B) method presented by Neron et al. (Omega 29(6):501-511, 2001). The results show that the improved ACO method is an effective and efficient method for solving HFS problems.en_US
dc.identifier.doi10.1007/s00170-007-1048-2en_US
dc.identifier.endpage550en_US
dc.identifier.issn0268-3768en_US
dc.identifier.issn1433-3015en_US
dc.identifier.issue05.06.2020en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage541en_US
dc.identifier.urihttps://dx.doi.org/10.1007/s00170-007-1048-2
dc.identifier.urihttps://hdl.handle.net/20.500.12395/21729
dc.identifier.volume35en_US
dc.identifier.wosWOS:000250836200011en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSPRINGER LONDON LTDen_US
dc.relation.ispartofINTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGYen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectant colony optimizationen_US
dc.subjectimproved ant systemen_US
dc.subjecthybrid flow shop schedulingen_US
dc.titleUsing ant colony optimization to solve hybrid flow shop scheduling problemsen_US
dc.typeArticleen_US

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