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Article: Bi-objective hybrid flow shop scheduling with common due date

TitleBi-objective hybrid flow shop scheduling with common due date
Authors
KeywordsHybrid flow shop scheduling
Multi-objective
Genetic algorithm
Common due date
Issue Date2021
PublisherSpringer Verlag. The Journal's web site is located at http://www.springer.com/business/operations+research/journal/12351
Citation
Operational Research, 2021, v. 21, p. 1153-1178 How to Cite?
AbstractIn this paper, the problem of hybrid flow shop scheduling with common due dates (HFSCDD) is studied, and the objectives are to minimize the total waiting time and the total earliness/tardiness issues that arise. This study was motivated by a real-life shop floor, with the predefined goal of meeting the requirements of the final product in many manufacturing industries. Where the final product is assembled from multiple components and, the assembly is only initiated when all components of the product are complete in number. These interrelated components have common due dates. In this study, we developed a mathematical model of HFSCDD which made up of “n” jobs that were processed in “m” machines, located on “I” stages by taking into consideration the common due dates. This problem is classified as being NP-hard, and so an efficient modified genetic algorithm is developed to solve it. The proposed modify GA is developed based on the NSGA II method for large sized problems. The results of the proposed algorithm have been compared with PSO and GA algorithms and showed that the proposed algorithm achieved better performance than existing solutions, since the waiting time and the earliness/tardiness are significantly reduced. This is facilitated by the simultaneous production of components for the same product.
Persistent Identifierhttp://hdl.handle.net/10722/269425
ISSN
2023 Impact Factor: 2.3
2023 SCImago Journal Rankings: 0.654
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLi, Z-
dc.contributor.authorZhong, RY-
dc.contributor.authorBarenji, AV-
dc.contributor.authorLiu, JJ-
dc.contributor.authorYu, CX-
dc.contributor.authorHuang, GQ-
dc.date.accessioned2019-04-24T08:07:26Z-
dc.date.available2019-04-24T08:07:26Z-
dc.date.issued2021-
dc.identifier.citationOperational Research, 2021, v. 21, p. 1153-1178-
dc.identifier.issn1109-2858-
dc.identifier.urihttp://hdl.handle.net/10722/269425-
dc.description.abstractIn this paper, the problem of hybrid flow shop scheduling with common due dates (HFSCDD) is studied, and the objectives are to minimize the total waiting time and the total earliness/tardiness issues that arise. This study was motivated by a real-life shop floor, with the predefined goal of meeting the requirements of the final product in many manufacturing industries. Where the final product is assembled from multiple components and, the assembly is only initiated when all components of the product are complete in number. These interrelated components have common due dates. In this study, we developed a mathematical model of HFSCDD which made up of “n” jobs that were processed in “m” machines, located on “I” stages by taking into consideration the common due dates. This problem is classified as being NP-hard, and so an efficient modified genetic algorithm is developed to solve it. The proposed modify GA is developed based on the NSGA II method for large sized problems. The results of the proposed algorithm have been compared with PSO and GA algorithms and showed that the proposed algorithm achieved better performance than existing solutions, since the waiting time and the earliness/tardiness are significantly reduced. This is facilitated by the simultaneous production of components for the same product.-
dc.languageeng-
dc.publisherSpringer Verlag. The Journal's web site is located at http://www.springer.com/business/operations+research/journal/12351-
dc.relation.ispartofOperational Research-
dc.rightsThis version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/[insert DOI]-
dc.subjectHybrid flow shop scheduling-
dc.subjectMulti-objective-
dc.subjectGenetic algorithm-
dc.subjectCommon due date-
dc.titleBi-objective hybrid flow shop scheduling with common due date-
dc.typeArticle-
dc.identifier.emailZhong, RY: zhongzry@hku.hk-
dc.identifier.emailHuang, GQ: gqhuang@hku.hk-
dc.identifier.authorityZhong, RY=rp02116-
dc.identifier.authorityHuang, GQ=rp00118-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/s12351-019-00470-8-
dc.identifier.scopuseid_2-s2.0-85062733136-
dc.identifier.hkuros297371-
dc.identifier.volume21-
dc.identifier.spage1153-
dc.identifier.epage1178-
dc.identifier.isiWOS:000653076600015-
dc.publisher.placeGermany-
dc.identifier.issnl1109-2858-

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