Please use this identifier to cite or link to this item: https://doi.org/10.1023/A:1022692631328
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dc.titleSexual selection for genetic algorithms
dc.contributor.authorGoh, K.S.
dc.contributor.authorLim, A.
dc.contributor.authorRodrigues, B.
dc.date.accessioned2013-07-04T07:32:17Z
dc.date.available2013-07-04T07:32:17Z
dc.date.issued2003
dc.identifier.citationGoh, K.S., Lim, A., Rodrigues, B. (2003). Sexual selection for genetic algorithms. Artificial Intelligence Review 19 (2) : 123-152. ScholarBank@NUS Repository. https://doi.org/10.1023/A:1022692631328
dc.identifier.issn02692821
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/39027
dc.description.abstractGenetic Algorithms (GA) have been widely used in operations research and optimization since first proposed. A typical GA comprises three stages, the encoding, the selection and the recombination stages. In this work, we focus our attention on the selection stage of GA, and review a few commonly employed selection schemes and their associated scaling functions. We also examine common problems and solution methods for such selection schemes. We then propose a new selection scheme inspired by sexual selection principles through female choice selection, and compare the performance of this new scheme with commonly used selection methods in solving some well-known problems including the Royal Road Problem, the Open Shop Scheduling Problem and the Job Shop Scheduling Problem.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1023/A:1022692631328
dc.sourceScopus
dc.subjectGenetic algorithm
dc.subjectScheduling
dc.subjectSelection
dc.typeArticle
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1023/A:1022692631328
dc.description.sourcetitleArtificial Intelligence Review
dc.description.volume19
dc.description.issue2
dc.description.page123-152
dc.description.codenAIRVE
dc.identifier.isiut000181393500001
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