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dc.contributor.authorYuchi, Mingen_US
dc.contributor.authorKim, Jong-Hwanen_US
dc.contributor.authorJo, Jun Hyungen_US
dc.contributor.editorJohn L. Casti, Melvin Scotten_US
dc.date.accessioned2017-05-03T13:22:06Z
dc.date.available2017-05-03T13:22:06Z
dc.date.issued2007en_US
dc.identifier.issn00963003en_US
dc.identifier.doi10.1016/j.amc.2007.01.027en_US
dc.identifier.urihttp://hdl.handle.net/10072/18503
dc.description.abstractA population ecology inspired parent selection strategy is proposed to improve the searching ability of evolutionary algorithms for numerical constrained optimization problems. This method is mainly used to help find an appropriate number of feasible parents for offspring generation. Based on the similar phenomenon in population ecology, the number of feasible parents has a sigmoid-type relationship with that of the feasible individuals. To implement the novel parent selection strategy, the population is divided into two groups according to the feasibility of the individuals: the feasible group and infeasible group. The evaluation and ranking of these two groups are performed separately. The dynamic penalty method, annealing penalty method and stochastic ranking method are tested with the parent selection strategy on 13 benchmark problems. The results show that the proposed method is capable of improving the searching performance.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_US
dc.languageEnglishen_US
dc.language.isoen_US
dc.publisherElsevieren_US
dc.publisher.placeAmsterdamen_US
dc.relation.ispartofstudentpublicationNen_US
dc.relation.ispartofpagefrom292en_US
dc.relation.ispartofpageto304en_US
dc.relation.ispartofissue1en_US
dc.relation.ispartofjournalApplied Mathematics and Computation (AMC)en_US
dc.relation.ispartofvolume190en_US
dc.rights.retentionYen_US
dc.subject.fieldofresearchcode280212en_US
dc.titleA population ecology inspired parent selection strategy for numerical constrained optimization problemsen_US
dc.typeJournal articleen_US
dc.type.descriptionC1 - Peer Reviewed (HERDC)en_US
dc.type.codeC - Journal Articlesen_US
gro.date.issued2015-02-12T00:42:58Z
gro.hasfulltextNo Full Text


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