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dc.contributor.authorLi, Y.Z.
dc.contributor.authorPan, Q.K.
dc.contributor.authorGao, K.Z.
dc.contributor.authorTasgetiren, M.F.
dc.contributor.authorZhang, B.
dc.contributor.authorLi, J.Q.
dc.date.accessioned2021-06-29T08:54:51Z
dc.date.available2021-06-29T08:54:51Z
dc.date.issued2021
dc.identifier.issn1568-4946
dc.identifier.urihttps://www.scopus.com/record/display.uri?eid=2-s2.0-85107089301&origin=SingleRecordEmailAlert&dgcid=raven_sc_search_en_us_email&txGid=711a41eb688c7760c830d05a83bb8286en_US
dc.identifier.urihttps://dspace.yasar.edu.tr/xmlui/handle/20.500.12742/11252
dc.description.abstractIn recent years, sustainable development and green manufacturing have attracted widespread attention to environmental problems becoming increasingly serious. Meanwhile, affected by the intensification of market competition and economic globalization, distributed manufacturing systems have become increasingly common. This paper addresses the energy-efficient scheduling of the distributed permutation flowshop (EEDPFSP) with the criteria of minimizing both total flow time and total energy consumption. Considering the distributed and multi-objective optimization complexity, an improved NSGAII algorithm (INSGAII) is proposed. First, we analyze the problem-specific characteristics and designed new operators based on the knowledge of the problem. Second, four constructive heuristic algorithms are proposed to produce high-quality initial solutions. Third, inspired by the artificial bee colony algorithm, we propose a new colony generation method using the operators designed. Fourth, a local intensification is designed for exploiting better non-dominated solutions. The influence of parameter settings is investigated by experiments to determine the optimal parameter configuration of the INSGAII. Finally, a large number of computational tests and comparisons have been carried out to verify the effectiveness of the proposed INSGAII in solving EEDPFSP.en_US
dc.language.isoEnglishen_US
dc.publisherElsevieren_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectDistributed permutation flowshop schedulingen_US
dc.subjectEnergy efficienten_US
dc.subjectMulti-objective optimizationen_US
dc.subjectNSGA-IIen_US
dc.subjectTotal energy consumptionen_US
dc.subjectTotal flowtimeen_US
dc.titleA green scheduling algorithm for the distributed flowshop problemen_US
dc.typeArticleen_US
dc.relation.journalApplied Soft Computingen_US
dc.identifier.doi10.1016/j.asoc.2021.107526en_US
dc.contributor.departmentDepartment of International Logistics Managementen_US
dc.identifier.issue109en_US
dc.contributor.yasarauthor0000-0002-5716-575X: Mehmet Fatih Taşgetirenen_US


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