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Drone Delivery Scheduling Optimization Considering Payload-induced Battery Consumption Rates

机译:考虑有效载荷诱导的电池消耗率的无人机交付调度优化

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This paper addresses the design of a parcel delivery system using drones, which includes the strategic planning of the system and operational planning for a given region. The amount of payload affects the battery consumption rate (BCR), which can cause a disruption in delivery of goods if the BCR was under-estimated in the planning stage or cause unnecessarily higher expenses if it was over-estimated. Hence, a reliable parcel delivery schedule using drones is proposed to consider the BCR as a function of payload in the operational planning optimization. A minimum set covering approach is used to model the strategic planning and a mixed integer linear programming problem (MILP) is used for operational planning. A variable preprocessing algorithm and primal and dual bound generation methods are developed to improve the computational time for solving the operational planning model. The optimal solution provides the least number of drones and their flight paths to deliver parcels while ensuring the safe return of the drones with respect to the battery charge level. Experimental data show that the BCR is a linear function of the payload amount. The results indicate the impact of including the BCR in drone scheduling, 3 out of 5 (60%) flight paths are not feasible if the BCR is not considered. The numerical results show that the sequence of visiting customers impacts the remaining charge.
机译:本文涉及使用无人机的包裹递送系统的设计,包括系统的战略规划和给定区域的运营计划。有效载荷量会影响电池消耗率(BCR),如果BCR在规划阶段估计,如果在规划阶段估计或者如果过度估计,则会导致货物的交付中断。因此,建议使用无人机的可靠性包裹递送计划,以考虑BCR作为操作计划优化中有效载荷的函数。最小集合覆盖方法用于模拟战略规划,并且混合整数线性编程问题(MILP)用于操作规划。开发了一种可变预处理算法和原始和双界生成方法,以改善解决操作计划模型的计算时间。最佳解决方案提供最少数量的无人机及其飞行路径,以提供包裹的同时确保无人机相对于电池充电水平的安全返回。实验数据表明,BCR是有效载荷量的线性函数。结果表明包括BCR在无人机调度中的影响,如果不考虑BCR,则为5(60%)的飞行路径是不可行的。数值结果表明,访问客户的序列会影响其余的费用。

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