Abstract: Logistics unmanned aerial vehicle（UAV） will encounter various uncertain interference factors in the actual delivery flight, which will lead to delivery delay. In order to reduce the loss caused by UAV delivery delay after being disturbed, a hybrid strategy of self-rescue, additional dispatch and cancellation is proposed. Meanwhile, a subsection model of UAV energy consumption is added to accurately calculate the flight energy consumption to ensure the feasibility of the delivery scheme. Firstly, the optimal scheduling scheme without interference is generated. Secondly, the number of the disturbed UAV, the disturbed time and the recovery time are randomly generated. The rescue strategy of the disturbed customer is taken as the decision variable, and the delivery completion rate and customer satisfaction are taken into account with the goal of minimizing the cost. The improved ant colony algorithm is used to solve the model. Finally, the Solomon example is used to test. The results show that compared with the global rescheduling strategy, the cost of self-rescue, additional dispatch and cancellation strategy is reduced by 11.5% on average, delivery completion rate is increased by 9.5% and customer satisfaction is increased by 7%. When solving small-scale examples, the new scheme generated by using mixed strategy not only reduces the distribution cost, but also improves the delivery completion rate and customer satisfaction, and minimizes the impact of interference as much as possible.

Key words: logistics UAV, disturbed, logistics scheduling, improved ant colony algorithm

摘要： 物流无人机在实际配送飞行中会遭遇各种不确定干扰因素，进而导致配送延误。为减小无人机受扰后配送延误带来的损失，提出自救、增派与取消的混合策略，同时加入无人机能耗分段模型，精确计算飞行所需能耗，确保配送方案切实可行。研究了生成无干扰时最优调度方案。随机生成受扰无人机编号、受扰时间与恢复所需时间，将受扰客户救援策略作为决策变量，以最小成本为目标兼顾交货完成率与客户满意度，使用改进蚁群算法对模型求解。运用所罗门算例进行测试。结果表明自救、增派与取消的混合策略较全局重调策略成本平均降低11.5%，交货完成率提高9.5%，客户满意度提高7%。在求解小规模算例时，使用混合策略生成的新方案不仅仅降低了配送成本，同时提高了交货完成率与客户满意度，尽可能使得干扰带来的影响最小。

关键词: 物流无人机, 受扰, 物流调度, 改进蚁群算法