Study on hybrid genetic algorithm for hybrid picking-delivery strategy vehicle routing problem

In order to satisfy with the individual and various demand of customer, establish 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 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. This algorithm has the characteristics of simple, clear and flexible and it can offer the thought to settle the practical problem in scale. At the same time, it can be known that adopting hybrid picking delivery strategy can save the distance of distribution route so as to reduce company operating cost and improve economic benefit.