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|Title:||A multiobjective evolutionary algorithm for solving vehicle routing problem with time windows|
|Authors:||Tan, K.C. |
|Keywords:||Multiobjective evolutionary optimization|
Vehicle routing with time windows
|Citation:||Tan, 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.|
|Abstract:||Vehicle 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.|
|Source Title:||Proceedings of the IEEE International Conference on Systems, Man and Cybernetics|
|Appears in Collections:||Staff Publications|
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