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A hybrid approach to vehicle routing using neural networks and genetic algorithms
Authors:Jean-Yves Potvin  Danny Dubé  Christian Robillard
Affiliation:(1) Centre de recherche sur les transports, Université de Montréal, Succ. Centre-Ville, C.P. 6128, H3C 3J7 Montréal, (Québec), Canada
Abstract:A competitive neural network model and a genetic algorithm are used to improve the initialization and construction phase of a parallel insertion heuristic for the vehicle routing problem with time windows. The neural network identifies seed customers that are distributed over the entire geographic area during the initialization phase, while the genetic algorithm finds good parameter settings in the route construction phase that follows. Computational results on a standard set of problems are also reported.
Keywords:vehicle routing  time windows  neural networks  genetic algorithms
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