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Conference Paper: A genetic algorithm for the minimum weight triangulation

TitleA genetic algorithm for the minimum weight triangulation
Authors
Keywordsgenetic algorithm
adaptive genetic operators
crossover
mutation
the minimum weight triangulation
Issue Date1997
PublisherIEEE.
Citation
IEEE International Conference on Evolutionary Computation Proceedings, Indianapolis, IN, 13-16 April 1997, p. 541-546 How to Cite?
AbstractIn this paper, a new method for the minimum weight triangulation of points on a plane, called genetic minimum weight triangulation (GMWT), is presented based on the rationale of genetic algorithms. Polygon crossover and its algorithm for triangulations are proposed. New adaptive genetic operators, or adaptive crossover and mutation operators, are introduced. It is shown that the new method for the minimum weight triangulation can obtain more optimal results of triangulations than the greedy algorithm.
Persistent Identifierhttp://hdl.handle.net/10722/45578

 

DC FieldValueLanguage
dc.contributor.authorQin, KHen_HK
dc.contributor.authorWang, WPen_HK
dc.contributor.authorGong, MLen_HK
dc.date.accessioned2007-10-30T06:29:35Z-
dc.date.available2007-10-30T06:29:35Z-
dc.date.issued1997en_HK
dc.identifier.citationIEEE International Conference on Evolutionary Computation Proceedings, Indianapolis, IN, 13-16 April 1997, p. 541-546en_HK
dc.identifier.urihttp://hdl.handle.net/10722/45578-
dc.description.abstractIn this paper, a new method for the minimum weight triangulation of points on a plane, called genetic minimum weight triangulation (GMWT), is presented based on the rationale of genetic algorithms. Polygon crossover and its algorithm for triangulations are proposed. New adaptive genetic operators, or adaptive crossover and mutation operators, are introduced. It is shown that the new method for the minimum weight triangulation can obtain more optimal results of triangulations than the greedy algorithm.en_HK
dc.format.extent531633 bytes-
dc.format.extent3373 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.relation.ispartofIEEE International Conference on Evolutionary Computation Proceedings-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rights©1997 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_HK
dc.subjectgenetic algorithmen_HK
dc.subjectadaptive genetic operatorsen_HK
dc.subjectcrossoveren_HK
dc.subjectmutationen_HK
dc.subjectthe minimum weight triangulationen_HK
dc.titleA genetic algorithm for the minimum weight triangulationen_HK
dc.typeConference_Paperen_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/ICEC.1997.592370en_HK
dc.identifier.hkuros27269-

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