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dc.contributor.authorTsai, HKen_US
dc.contributor.authorYang, JMen_US
dc.contributor.authorTsai, YFen_US
dc.contributor.authorKao, CYen_US
dc.date.accessioned2014-12-08T15:37:19Z-
dc.date.available2014-12-08T15:37:19Z-
dc.date.issued2004-11-01en_US
dc.identifier.issn1432-7643en_US
dc.identifier.urihttp://dx.doi.org/10.1007/s00500-003-0317-8en_US
dc.identifier.urihttp://hdl.handle.net/11536/25658-
dc.description.abstractThis paper demonstrates that a robust genetic algorithm for the traveling salesman problem (TSP) should preserve and add good edges efficiently, and at the same time, maintain the population diversity well. We analyzed the strengths and limitations of several well-known genetic operators for TSPs by the experiments. To evaluate these factors, we propose a new genetic algorithm integrating two genetic operators and a heterogeneous pairing selection. The former can preserve and add good edges efficiently and the later will be able to keep the population diversity. The proposed approach was evaluated on 15 well-known TSPs whose numbers of cities range from 101 to 13509. Experimental results indicated that our approach, somewhat slower, performs very robustly and is very competitive with other approaches in our best surveys. We believe that a genetic algorithm can be a stable approach for TSPs if its operators can preserve and add edges efficiently and it maintains population diversity.en_US
dc.language.isoen_USen_US
dc.subjectedge assembly crossoveren_US
dc.subjectheterogeneous pairing selectionen_US
dc.subjectgenetic algorithmen_US
dc.subjectneighbor-join mutationen_US
dc.subjecttraveling salesman problemen_US
dc.titleSome issues of designing genetic algorithms for traveling salesman problemsen_US
dc.typeArticleen_US
dc.identifier.doi10.1007/s00500-003-0317-8en_US
dc.identifier.journalSOFT COMPUTINGen_US
dc.citation.volume8en_US
dc.citation.issue10en_US
dc.citation.spage689en_US
dc.citation.epage697en_US
dc.contributor.department生物科技學系zh_TW
dc.contributor.department生物資訊及系統生物研究所zh_TW
dc.contributor.departmentDepartment of Biological Science and Technologyen_US
dc.contributor.departmentInstitude of Bioinformatics and Systems Biologyen_US
dc.identifier.wosnumberWOS:000226545500008-
dc.citation.woscount6-
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