改进混合粒子群算法求解带时间窗的 无人机与车辆协同路径调度问题.

In order to improve the delivery efficiency of logistics, this paper proposed a vehicle routing problem with drone and time window considered by the time window, UAV (unmanned aerial vehicle) power change and multi-point continuous delivery of UAV. Then, this paper proposed a hybrid particle swarm optimization algorithm with local search to solve it. Based on the hybrid particle swarm optimization algorithm, the proposed algorithm transformed the problem solution space into the algorithm search space by constructing an efficient encoding and decoding strategy. Further, the proposed algorithm combined a single point insertion strategy, a vehicle replacement strategy and a UAV replacement strategy to form a local search strategy to improve the optimization ability. The experimental results show that the proposed model is more efficient than the model of pure vehicle distribution and saves 31.51% of the cost. The proposed algorithm is better than the four comparison algorithms, and its highest optimization rate is 82.08%. [ABSTRACT FROM AUTHOR]