An iterated greedy algorithm for the distributed permutation flowshop scheduling problem with preventive maintenance to minimize total flowtime

dc.contributor.author Jiayang Mao
dc.contributor.author XiaoLu Hu
dc.contributor.author Quan-ke Pan
dc.contributor.author Zhonghua Miao
dc.contributor.author Chuangxin He
dc.contributor.author M. Fatih Tasgetiren
dc.contributor.author Tasgetiren, M. Fatih
dc.contributor.author He, Chuangxin
dc.contributor.author Mao, Jiayang
dc.contributor.author Hu, XiaoLu
dc.contributor.author Pan, Quan-ke
dc.contributor.author Miao, Zhonghua
dc.contributor.editor J Fu
dc.contributor.editor J Sun
dc.coverage.spatial 39th Chinese Control Conference (CCC)
dc.date.accessioned 2025-10-06T16:21:35Z
dc.date.issued 2020
dc.description.abstract In recent years the distributed permutation flowshop scheduling problem (DPFSP) has been widely studied. In this paper we extended the DPFSP by considering preventive maintenance (PM) operation to prevent machines from breaking down after the long process. An iterated greedy (IG) algorithm is developed to minimize total flowtime. A heuristic with swapping operator is proposed to initialize the IG. After that the destruction phase and construction phase are modified to fit our problem. A local search is then applied to further improve the solution generated in the construction stage. At last a simple simulated annealing-like acceptance criterion is used to prevent local optimal situations. Comparison with three state-of-the art algorithms in the recent literature based on 225 instances shows the high performance of our IG algorithm for solving the DPFSP with PM operation.
dc.description.sponsorship This research is partially supported by the National Science Foundation of China 61973203 and 51575212 and and Shanghai Key Laboratory of Power station Automation Technology.
dc.description.sponsorship National Science Foundation of China [61973203, 51575212]; Shanghai Key Laboratory of Power station Automation Technology
dc.identifier.isbn 978-988-15639-0-3
dc.identifier.isbn 9789881563903
dc.identifier.issn 2161-2927
dc.identifier.uri https://gcris.yasar.edu.tr/handle/123456789/6935
dc.language.iso English
dc.publisher IEEE
dc.relation.ispartof 39th Chinese Control Conference (CCC)
dc.relation.ispartofseries Chinese Control Conference
dc.rights info:eu-repo/semantics/closedAccess
dc.source PROCEEDINGS OF THE 39TH CHINESE CONTROL CONFERENCE
dc.subject Distributed scheduling, Flowshop, Preventive maintenance
dc.subject MAKESPAN, METAHEURISTICS, HEURISTICS, MACHINE
dc.subject Flowshop
dc.subject Distributed Scheduling
dc.subject Preventive Maintenance
dc.title An iterated greedy algorithm for the distributed permutation flowshop scheduling problem with preventive maintenance to minimize total flowtime
dc.type Conference Object
dspace.entity.type Publication
gdc.author.id Mao, Jiayang/0009-0009-9565-5854
gdc.author.id Tasgetiren, M Fatih/0000-0001-8625-3671
gdc.author.id Pan, QUAN-KE/0000-0002-5022-7946
gdc.author.id Tasgetiren, Mehmet Fatih/0000-0002-5716-575X
gdc.author.wosid Pan, QUAN-KE/F-2019-2013
gdc.coar.type text::conference output
gdc.description.department
gdc.description.departmenttemp [Mao, Jiayang; Pan, Quan-ke; Miao, Zhonghua; He, Chuangxin] Shanghai Univ, Sch Mech & Elect Engn & Automat, Shanghai 200444, Peoples R China; [Hu, XiaoLu] China Rural Technol Dev Ctr, Beijing 100045, Peoples R China; [Tasgetiren, M. Fatih] Yasar Univ, Int Logist Management Dept, Izmir, Turkey
gdc.description.endpage CP1
gdc.description.publicationcategory Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
gdc.description.startpage CP1
gdc.description.woscitationindex Conference Proceedings Citation Index - Science
gdc.identifier.wos WOS:000629243501109
gdc.index.type WoS
gdc.wos.citedcount 6
oaire.citation.endPage CP1
oaire.citation.startPage CP1
project.funder.name National Science Foundation of China [61973203- 51575212], Shanghai Key Laboratory of Power station Automation Technology
relation.isOrgUnitOfPublication ac5ddece-c76d-476d-ab30-e4d3029dee37
relation.isOrgUnitOfPublication.latestForDiscovery ac5ddece-c76d-476d-ab30-e4d3029dee37

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