随着互联网的快速发展如今物流企业的业务也出现各种不同的需求为给物流行业提供更贴合实际的决策支持针对于单中心情形研究带时间窗的同时送取货车辆路径问题VRPSPDTW。对于该问题的求解提出了基于布谷鸟算法的一种新型改进的自适应离散布谷鸟算法Adaptive Discrete Cuckoo SearchADCS。该算法在标准的布谷鸟算法的基础上使用了路径间搜索swapshift路径内搜索relocate

Translation:

With the rapid development of the Internet, various different needs have arisen in the logistics industry. In order to provide more practical decision support for logistics, a study has been conducted on the Vehicle Routing Problem with Simultaneous Pickup and Delivery and Time Windows (VRPSPDTW) for single centers. A new type of improved adaptive discrete cuckoo search algorithm (ADCS) based on the cuckoo search algorithm has been proposed for solving this problem. The algorithm uses path-interchange (swap/shift), path-intra-search (relocate/exchange), and differential weight-grouping (weight-differential restructuring) to replace the original nest updating mechanism of flight, and in this phase, the adaptive selection of the operator is used to improve the search ability of the algorithm. In the parasitic nest updating process, recombination and competition/elimination mechanisms are used to replace the preference random walk in the standard algorithm. In the simulation experiment stage, 56 large-scale cases were selected to test the performance of the algorithm, and comparative experiments were conducted with other intelligent optimization algorithms such as GA algorithm, p-SA algorithm, VNS-BSTS algorithm, ALNS-PR algorithm, and DSC algorithm. 26 of the cases updated the current international optimal solution. The results show the feasibility and superiority of the algorithm in solving the VRPSPDTW problem, and enrich the relevant research on vehicle routing problems