Shi Yuhe, Lin Yun, Li Bo, Yi Man Li Rita
School of Management Science and Real Estate, Chongqing University, Chongqing 400000, People's Republic of China.
Chakrabongse Bhuvanarth International Institute for Interdisciplinary Studies, Rajamangala University of Technology Tawan-Ok, Bangkok 10400, Thailand.
Comput Ind Eng. 2022 Sep;171:108389. doi: 10.1016/j.cie.2022.108389. Epub 2022 Jun 30.
In the COVID-19 pandemic, it is essential to transport medical supplies to specific locations accurately, safely, and promptly on time. The application of drones for medical supplies delivery can break ground traffic restrictions, shorten delivery time, and achieve the goal of contactless delivery to reduce the likelihood of contacting COVID-19 patients. However, the existing optimization model for drone delivery is cannot meet the requirements of medical supplies delivery in public health emergencies. Therefore, this paper proposes a bi-objective mixed integer programming model for the multi-trip drone location routing problem, which allows simultaneous pick-up and delivery, and shorten the time to deliver medical supplies in the right place. Then, a modified NSGA-II (Non-dominated Sorting Genetic Algorithm II) which includes double-layer coding, is designed to solve the model. This paper also conducts multiple sets of data experiments to verify the performance of modified NSGA-II. Comparing with separate pickup and delivery modes, this study demonstrates that the proposed optimization model with simultaneous pickup and delivery mode achieves a shorter time, is safer, and saves more resources. Finally, the sensitivity analysis is conducted by changing some parameters, and providing some reference suggestions for medical supplies delivery management via drones.
在新冠疫情期间,准确、安全且及时地将医疗物资准时运送到特定地点至关重要。无人机用于医疗物资配送可突破地面交通限制,缩短配送时间,并实现无接触配送目标,以降低接触新冠患者的可能性。然而,现有的无人机配送优化模型无法满足突发公共卫生事件中医疗物资配送的要求。因此,本文针对多趟次无人机定位路径问题提出了一种双目标混合整数规划模型,该模型允许同时取货和送货,并缩短将医疗物资送达正确地点的时间。然后,设计了一种包含双层编码的改进型NSGA-II(非支配排序遗传算法II)来求解该模型。本文还进行了多组数据实验以验证改进型NSGA-II的性能。与单独的取货和送货模式相比,本研究表明所提出的同时取货和送货模式的优化模型实现了更短的时间、更安全且节省了更多资源。最后,通过改变一些参数进行敏感性分析,并为无人机医疗物资配送管理提供一些参考建议。