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dc.contributor.authorMirjalili, Seyedali
dc.contributor.authorSaremi, Shahrzad
dc.contributor.authorMirjalili, Seyed Mohammad
dc.contributor.authorCoelho, Leandro dos S
dc.date.accessioned2018-07-19T05:02:51Z
dc.date.available2018-07-19T05:02:51Z
dc.date.issued2016
dc.identifier.issn0957-4174
dc.identifier.doi10.1016/j.eswa.2015.10.039
dc.identifier.urihttp://hdl.handle.net/10072/99973
dc.description.abstractDue to the novelty of the Grey Wolf Optimizer (GWO), there is no study in the literature to design a multi-objective version of this algorithm. This paper proposes a Multi-Objective Grey Wolf Optimizer (MOGWO) in order to optimize problems with multiple objectives for the first time. A fixed-sized external archive is integrated to the GWO for saving and retrieving the Pareto optimal solutions. This archive is then employed to define the social hierarchy and simulate the hunting behavior of grey wolves in multi-objective search spaces. The proposed method is tested on 10 multi-objective benchmark problems and compared with two well-known meta-heuristics: Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D) and Multi-Objective Particle Swarm Optimization (MOPSO). The qualitative and quantitative results show that the proposed algorithm is able to provide very competitive results and outperforms other algorithms. Note that the source codes of MOGWO are publicly available at http://www.alimirjalili.com/GWO.html.
dc.description.peerreviewedYes
dc.languageEnglish
dc.language.isoeng
dc.publisherElsevier
dc.relation.ispartofpagefrom106
dc.relation.ispartofpageto119
dc.relation.ispartofjournalExpert Systems With Applications
dc.relation.ispartofvolume47
dc.subject.fieldofresearchMathematical Sciences not elsewhere classified
dc.subject.fieldofresearchMathematical Sciences
dc.subject.fieldofresearchInformation and Computing Sciences
dc.subject.fieldofresearchEngineering
dc.subject.fieldofresearchcode019999
dc.subject.fieldofresearchcode01
dc.subject.fieldofresearchcode08
dc.subject.fieldofresearchcode09
dc.titleMulti-objective grey wolf optimizer: A novel algorithm for multi-criterion optimization
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.facultyGriffith Sciences, School of Information and Communication Technology
gro.hasfulltextNo Full Text
gro.griffith.authorSaremi, Shahrzad
gro.griffith.authorMirjalili, Seyedali


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