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dc.contributor.authorGarcía-León, Andrés Alberto
dc.contributor.authorDauzère-Pérès, Stéphane
dc.contributor.authorMati, Yazid
dc.date.accessioned2019-06-26T13:31:54Z
dc.date.available2019-06-26T13:31:54Z
dc.date.created2019-05-24T09:16:51Z
dc.date.issued2019
dc.identifier.citationComputers & Operations Research. 2019, 108 187-200.nb_NO
dc.identifier.issn0305-0548
dc.identifier.urihttp://hdl.handle.net/11250/2602386
dc.description.abstractIn this paper, a general local search approach for the Multi-Objective Flexible Job-shop Scheduling Problem (MOFJSP) is proposed to determine a Pareto front for any combination of regular criteria. The approach is based on a disjunctive graph, a fast estimation function to evaluate moves and a hierarchical test to efficiently control the set of non-dominated solutions. Four search strategies using two neighborhood structures are developed. Numerical experiments are conducted on test instances of the literature with three sets of criteria to minimize and using metrics to evaluate and compare Pareto fronts. The results show that our approach provides sets of non-dominated solutions of good quality.nb_NO
dc.language.isoengnb_NO
dc.publisherElseviernb_NO
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.no*
dc.titleAn efficient Pareto approach for solving the multi-objective flexible job-shop scheduling problem with regular criterianb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionpublishedVersionnb_NO
dc.source.pagenumber187-200nb_NO
dc.source.volume108nb_NO
dc.source.journalComputers & Operations Researchnb_NO
dc.identifier.doi10.1016/j.cor.2019.04.012
dc.identifier.cristin1699975
cristin.unitcode158,13,0,0
cristin.unitnameInstitutt for regnskap, revisjon og foretaksøkonomi
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode2


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Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal