Algorithm study of multiple-depot vehicle routing problem based on fuzzy simulation

In this paper, the multiple-depot vehicle routing problem with fuzzy demands is considered, on the basis of uncertain demand of multiple-depot vehicle routing problem, a fuzzy chance constrained program is designed based on fuzzy credibility theory. Then the hybrid genetic algorithm based on fuzzy simulation is used to solve the vehicle routing model. In genetic algorithm, a new code is given, and introduce an evolution method that combining evolution of same depot vehicle and different depot vehicle, in order to avoid local constringency and get general optimization. The results of experiment indicated that the algorithm can effectively solve the fuzzy vehicle routing problem.