Study on hybrid genetic algorithm for multi-type vehicles vehicle routing problem with backhauls

Abstract

In order to satisfy with the individual and various demand of customer, establish Multi-type Vehicles Vehicle scheduling with picking-delivery model. According to the characteristics of model, hybrid genetic algorithm is used to get the optimization solution. First of all, use natural number coding so as to simplify the problem; use the individual amount control choice strategy so as to guarantee the diversity of group. Improved ordinal crossover operators can avoid destroying good gene parts during the course of ordinal crossover so as that the algorithm can be convergent to the optimization as whole. The study adopts 2- exchange mutation operator combine hill-climbing algorithm to strengthen the partial searching ability of chromosome. Secondly, stock elite adopting genetic algorithm take the hybrid genetic algorithm with taboo searching algorithm to improve the convergent speed and searching efficiency of algorithm. The emulation and calculation proves that it is better than only using genetic algorithm and taboo searching algorithm.