关键词: 车辆路径规划, 遗传算法, 反向传播（BP）算法, 改进混合算法

Abstract: Aiming to the requirements to find the shortest path among distribution nodes in logistics activities to guide logistics vehicle scheduling, this paper provides a new method which combines genetic algorithm and BP algorithm for vehicle path planning to achieve the goal of saving transporting cost. In this paper, the genetic algorithm is improved, and the shortcomings of the genetic algorithm, such as poor local search capability, easy to be early-maturing and not good enough global feasible solution, are covered. This hybrid algorithm covers the shortage of genetic algorithm efficiently, and adopts the optimal preservation strategy in the genetic optimize operation and tournament selection method in the selection operation, which improves the efficiency and function of the algorithm highly. Through the simulation to the performance of this improved hybrid algorithm of vehicle path planning based on genetic algorithm, and compared with adaptive genetic algorithm and immune genetic algorithm, and analyzing the results, the advantages and effectiveness of the hybrid algorithm are proved.

Key words: vehicle routing problem, genetic algorithm, Back Propagation（BP） algorithm, improved hybrid algorithm