Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.advengsoft.2005.10.003
DC FieldValue
dc.titleSolving the feeder bus network design problem by genetic algorithms and ant colony optimization
dc.contributor.authorKuan, S.N.
dc.contributor.authorOng, H.L.
dc.contributor.authorNg, K.M.
dc.date.accessioned2014-06-17T07:02:47Z
dc.date.available2014-06-17T07:02:47Z
dc.date.issued2006-06
dc.identifier.citationKuan, S.N., Ong, H.L., Ng, K.M. (2006-06). Solving the feeder bus network design problem by genetic algorithms and ant colony optimization. Advances in Engineering Software 37 (6) : 351-359. ScholarBank@NUS Repository. https://doi.org/10.1016/j.advengsoft.2005.10.003
dc.identifier.issn09659978
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/63327
dc.description.abstractThis paper proposes the design and analysis of two metaheuristics, genetic algorithms and ant colony optimization, for solving the feeder bus network design problem. A study of how these proposed heuristics perform is carried out on several randomly generated test problems to evaluate their computational efficiency and the quality of solutions obtained by them. The results are also compared to those published in the literature. Computational experiments have shown that both heuristics are comparable to the state-of-the-art algorithms such as simulated annealing and tabu search. © 2005 Elsevier Ltd. All rights reserved.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/j.advengsoft.2005.10.003
dc.sourceScopus
dc.subjectAnt colony optimization
dc.subjectFeeder bus
dc.subjectGenetic algorithm
dc.subjectMetaheuristics
dc.typeArticle
dc.contributor.departmentINDUSTRIAL & SYSTEMS ENGINEERING
dc.description.doi10.1016/j.advengsoft.2005.10.003
dc.description.sourcetitleAdvances in Engineering Software
dc.description.volume37
dc.description.issue6
dc.description.page351-359
dc.description.codenAESOD
dc.identifier.isiut000237016600001
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