A Hybrid Multiobjective Evolutionary Algorithm for Solving Vehicle Routing Problem with Time Windows
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چکیده
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 customers with known demands and predefined time windows. Routes for the vehicles must meet all given constraints as well as minimize the objectives of travel distance and vehicles numbers. We proposed hybrid multiobjective evolutionary algorithm (HMOEA) incorporates simple heuristics for local exploitation and the concept of Pareto's optimality for solving multiobjective optimization in VRPTW. It is featured with specialized evolutionary operators and variable-length chromosome representation to accommodate the sequence oriented optimization in VRPTW. The HMOEA improves the routing solutions in many aspects, such as lower routing cost, better population distribution, wider scattering area and good convergence trace.
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