Hybrid flow shop with multiprocessor task scheduling based on earliness and tardiness penalties

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dc.contributor.authorEngin, Orhan
dc.contributor.authorEngin, Batuhan
dc.date.accessioned2020-03-26T19:54:12Z
dc.date.available2020-03-26T19:54:12Z
dc.date.issued2018
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractPurpose Hybrid flow shop with multiprocessor task (HFSMT) has received considerable attention in recent years. The purpose of this paper is to consider an HFSMT scheduling under the environment of a common time window. The window size and location are considered to be given parameters. The research deals with the criterion of total penalty cost minimization incurred by earliness and tardiness of jobs. In this research, a new memetic algorithm in which a global search algorithm is accompanied with the local search mechanism is developed to solve the HFSMT with jobs having a common time window. The operating parameters of memetic algorithm have an important role on the quality of solution. In this paper, a full factorial experimental design is used to determining the best parameters of memetic algorithm for each problem type. Memetic algorithm is tested using HFSMT problems. Design/methodology/approach First, hybrid flow shop scheduling system and hybrid flow shop scheduling with multiprocessor task are defined. The applications of the hybrid flow shop system are explained. Also the background of hybrid flow shop with multiprocessor is given in the introduction. The features of the proposed memetic algorithm are described in Section 2. The experiment results are presented in Section 3. Findings Computational experiments show that the proposed new memetic algorithm is an effective and efficient approach for solving the HFSMT under the environment of a common time window. Originality/value There is only one study about HFSMT scheduling with time window. This is the first study which added the windows to the jobs in HFSMT problems.en_US
dc.identifier.doi10.1108/JEIM-04-2017-0051en_US
dc.identifier.endpage936en_US
dc.identifier.issn1741-0398en_US
dc.identifier.issn1758-7409en_US
dc.identifier.issue6en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage925en_US
dc.identifier.urihttps://dx.doi.org/10.1108/JEIM-04-2017-0051
dc.identifier.urihttps://hdl.handle.net/20.500.12395/36682
dc.identifier.volume31en_US
dc.identifier.wosWOS:000446849100008en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherEMERALD GROUP PUBLISHING LTDen_US
dc.relation.ispartofJOURNAL OF ENTERPRISE INFORMATION MANAGEMENTen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectMemetic algorithmen_US
dc.subjectHybrid flow shopen_US
dc.subjectMultiprocessor tasken_US
dc.subjectTime windowen_US
dc.titleHybrid flow shop with multiprocessor task scheduling based on earliness and tardiness penaltiesen_US
dc.typeArticleen_US

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