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Please use this identifier to cite or link to this item: https://doi.org/10.1103/PhysRevE.70.016701
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dc.titleGeneralized chromosome genetic algorithm for generalized traveling salesman problems and its applications for machining
dc.contributor.authorWu, C.
dc.contributor.authorLiang, Y.
dc.contributor.authorLee, H.P.
dc.contributor.authorLu, C.
dc.date.accessioned2014-06-17T06:22:43Z
dc.date.available2014-06-17T06:22:43Z
dc.date.issued2004-07
dc.identifier.citationWu, C., Liang, Y., Lee, H.P., Lu, C. (2004-07). Generalized chromosome genetic algorithm for generalized traveling salesman problems and its applications for machining. Physical Review E - Statistical, Nonlinear, and Soft Matter Physics 70 (1 2) : 016701-1. ScholarBank@NUS Repository. https://doi.org/10.1103/PhysRevE.70.016701
dc.identifier.issn15393755
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/60397
dc.description.abstractThe structure of conventional chromosome was generalized to be a chromosome termed as a generalized chromosome (GC). A genetic scheme named as generalized-chromosome-based genetic algorithm (GCGA) was also presented. It was found that the proposed GCGA enables GTSP and TSP to be solved under a uniform algorithm mode. The results show that GCGA can directly solve GTSP without the need of intermediate transformation to TSP.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1103/PhysRevE.70.016701
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentMECHANICAL ENGINEERING
dc.description.doi10.1103/PhysRevE.70.016701
dc.description.sourcetitlePhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
dc.description.volume70
dc.description.issue1 2
dc.description.page016701-1
dc.description.codenPLEEE
dc.identifier.isiut000223135800089
Appears in Collections:Staff Publications

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