【摘要】 以现代物流领域中使用卡车和无人机进行末端配送为背景，为商用物流配送企业提供卡车与无人机同步配送的新方案，针对卡车无人机配送的成本较高且效率较低问题，考虑了无人机有效载荷、飞行状态对无人机能耗及实际飞行航程的影响，对非同步运行模型进行改进，提出了考虑无人机能耗的卡车无人机同步运行选址模型，利用粒子群算法求解，通过对比不同载荷，飞行状态，客户点规模和运行模式下的差异证明了本文的配送模式下无人机能耗对选址结果的影响，并使传统卡车配送最低选址成本分别降低了20.67%,25.77%,29.14%和19.47%,增强配送的时效性及准确率，为未来物流配送一体化研究提供依据.更多还原

【Abstract】 In the context of last-mile delivery in the modern logistics field, presented a new solution for commercial logistics delivery companies that integrated truck and drone collaboration. Addressing the issue of high costs and low efficiency in truck-drone delivery, considered the impact of drone payload and flight status on drone energy consumption and actual flight range. Improved the asynchronous operation model and proposed a truck-drone synchronized operation location selection model that took into account drone energy consumption, which was solved using a particle swarm algorithm. By comparing different payload capacities, flight statuses, customer point scales, and operation modes, this paper demonstrated the impact of drone energy consumption on location selection results. As a result, it achieved a reduction in the minimum site selection cost for traditional truck deliveries by 20.67%, 25.77%, 29.14%, and 19.47% for different payload capacities, flight statuses, customer point scales, and operation modes, respectively. This enhanced the efficiency and accuracy of the delivery system and provided a foundation for future research in integrated logistics and delivery.更多还原