Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/51085
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dc.titleA multiobjective evolutionary algorithm for solving vehicle routing problem with time windows
dc.contributor.authorTan, K.C.
dc.contributor.authorLee, T.H.
dc.contributor.authorChew, Y.H.
dc.contributor.authorLee, L.H.
dc.date.accessioned2014-04-24T08:32:44Z
dc.date.available2014-04-24T08:32:44Z
dc.date.issued2003
dc.identifier.citationTan, K.C.,Lee, T.H.,Chew, Y.H.,Lee, L.H. (2003). A multiobjective evolutionary algorithm for solving vehicle routing problem with time windows. Proceedings of the IEEE International Conference on Systems, Man and Cybernetics 1 : 361-366. ScholarBank@NUS Repository.
dc.identifier.issn08843627
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/51085
dc.description.abstractVehicle routing problem with time windows (VRPTW) involves the routing of a set of vehicles with limited capacity from a central depot to a set of geographically dispersed customers with known demands and predefined time windows. This paper proposes a hybrid multiobjective evolutionary algorithm (HMOEA) that incorporates various heuristics for local exploitation in the evolutionary search and the concept of Pareto's optimality for solving multiobjective optimization in VRPTW problems. The proposed HMOEA optimizes all routing constraints and objectives simultaneously, which improves the routing solutions in many aspects, such as lower routing cost, wider scattering area and better convergence trace.
dc.sourceScopus
dc.subjectMultiobjective evolutionary optimization
dc.subjectVehicle routing with time windows
dc.typeConference Paper
dc.contributor.departmentINDUSTRIAL & SYSTEMS ENGINEERING
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.sourcetitleProceedings of the IEEE International Conference on Systems, Man and Cybernetics
dc.description.volume1
dc.description.page361-366
dc.description.codenPICYE
dc.identifier.isiutNOT_IN_WOS
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