Research on vehicle routing problem based on improved hybrid genetic algorithm

Vehicle route problem of logistics distribution is the important step optimizing logistics distribution. According to the traditional genetic algorithm shortcomings of slowly convergent speed, weakly partial searching ability and easily premature, therefore, hybrid genetic algorithm is used to get the optimization solution, namely, use dualistic coding so as to simplify the problem and improve the searching efficiency of genetic algorithm. The individual amount control choice strategy so as to guard the diversity of group. Improved route 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. Adopt self-adaptive thought to strengthen the partial searching ability of chromosome, combine hill-climbing algorithm, and improve the convergent speed of algorithm. Finally, the good performance of improved algorithm can be proved by experiment calculation and concrete examples.