无人机部署Optimization，用于带时间窗和电池更换的直接交付
Drone Deployment Optimization for Direct Delivery with Time Windows and Battery Replacements
摘要：
空中无人机提供了一个独特的潜力，以减少交付时间和能源消耗的时间敏感和小产品的交付。然而，相关行业仍需要了解在不同业务需求和无人机运行条件下，基于无人机的交付性能。我们研究了一个无人机部署最优化问题，直接交付货物给客户保持指定的时间窗口。本文提出了一种新的基于数学优化的决策方法，以帮助企业主优化其无人机机队的路线，最大限度地减少总能耗，所需的机队规模和所需的额外电池数量。该最优化方法的现实特征是，代替在每次返回到仓库之后更换无人机电池，它跟踪无人机电池中的剩余能量，并且考虑无人机路线和用户指定的最小所需电池能量来决定电池更换。基于真实无人机飞行测试和交付数据的数值结果提供了对不同无人机操作参数对能耗、所需机队规模和所需电池更换次数的影响的见解。案例研究的结果表明，与直线飞行相比，无人机在道路网络上飞行时，总能耗、所需机队规模和所需电池更换次数分别增加了72.22%、22.2%和200%。此外，结果表明，与使用仅由六轴飞行器组成的同质机群相比，使用六轴飞行器和四轴飞行器无人机的混合机群减少了48.52%的总能耗。
英文摘要：
Aerial drones offer a distinct potential to reduce the delivery time and energy consumption for the delivery of time-sensitive and small products. However, there is still a need in the relevant industry to understand the performance of drone-based delivery under different business needs and drone operating conditions. We studied a drone deployment optimization problem for direct delivery of goods to customers maintaining a specified time window. This paper presents a new mathematical optimization-based decision-making methodology to help business owners optimally route their drone fleet minimizing the total energy consumption, required fleet size, and the required number of additional batteries. A realistic feature of the optimization method is that instead of replacing the drone battery after each return to the depot, it keeps track of the remaining energy in the drone battery and decides on battery replacements accounting for the drone routing and the user-specified minimum required battery energy. Numerical results based on real drone flight tests and delivery data provide insights into the effect of different drone operating parameters on the energy consumption, required fleet size, and the required number of battery replacements. Results from a case study show that the total energy consumption, required fleet size, and the required number of battery replacements increase by 72.22%, 22.2%, and 200%, respectively, as the drones fly over the road networks compared to flying in a straight path. Additionally, results show that using a mixed fleet of hexacopter and quadcopter drones reduces the total energy consumption by 48.52% compared to using a homogeneous fleet of only hexacopters.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
