Optimizing last-mile delivery services: a robust truck-drone cooperation model and hybrid metaheuristic algorithm

IF 4.4 3区 管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE
Seyed Mohammad Javad Mirzapour Al-e-Hashem, Taha-Hossein Hejazi, Ghazal Haghverdizadeh, Mohsen Shidpour
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Abstract

In response to the increasing demand for faster customer service and cost-effective solutions in competitive markets, many companies are exploring strategies and tools to streamline their services. One emerging approach involves the integration of drones with trucks, offering potential benefits such as reduced environmental impact and delivery time. This study focuses on the use of a single truck coordinating with multiple drones for postal package delivery. The drones are transported by the truck, and both vehicles are responsible for carrying out deliveries. To account for weather uncertainties, specifically wind direction and speed affecting drone travel time, a robust optimization model is developed to address the truck-drone routing problem. Additionally, a hybrid metaheuristic algorithm is proposed, combining Adaptive Large Neighborhood Search, Clarke and Wright Saving Algorithm, and Genetic Algorithm. The effectiveness of this algorithm is assessed through numerical experiments, including sensitivity analyses on key problem parameters. The findings demonstrate that the proposed model has practical applications in last-mile delivery services, while the algorithm provides near-optimal solutions within a reasonable timeframe (ALNS reaches the solutions 3500% faster than GAMS for small-sized problems in average). Also the results show that with the 100% increase in average distance between nodes in the network, the service time increases by more than 200%.

Abstract Image

优化最后一英里配送服务:稳健的卡车-无人机合作模型和混合元启发式算法
为了满足竞争激烈的市场对更快的客户服务和具有成本效益的解决方案日益增长的需求,许多公司正在探索简化服务的战略和工具。一种新出现的方法是将无人机与卡车整合在一起,从而带来潜在的好处,如减少对环境的影响和缩短投递时间。本研究的重点是使用一辆卡车协调多架无人机进行邮政包裹递送。无人机由卡车运输,两辆车都负责送货。为了考虑天气的不确定性,特别是影响无人机飞行时间的风向和风速,开发了一个稳健的优化模型来解决卡车-无人机路由问题。此外,还提出了一种混合元启发式算法,该算法结合了自适应大邻域搜索、克拉克和莱特节省算法以及遗传算法。通过数值实验,包括关键问题参数的敏感性分析,对该算法的有效性进行了评估。实验结果表明,所提出的模型在最后一英里配送服务中具有实际应用价值,同时该算法能在合理的时间范围内提供接近最优的解决方案(对于小型问题,ALNS 的求解速度比 GAMS 平均快 3500%)。结果还显示,网络中节点之间的平均距离增加 100%,服务时间就会增加 200%以上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Annals of Operations Research
Annals of Operations Research 管理科学-运筹学与管理科学
CiteScore
7.90
自引率
16.70%
发文量
596
审稿时长
8.4 months
期刊介绍: The Annals of Operations Research publishes peer-reviewed original articles dealing with key aspects of operations research, including theory, practice, and computation. The journal publishes full-length research articles, short notes, expositions and surveys, reports on computational studies, and case studies that present new and innovative practical applications. In addition to regular issues, the journal publishes periodic special volumes that focus on defined fields of operations research, ranging from the highly theoretical to the algorithmic and the applied. These volumes have one or more Guest Editors who are responsible for collecting the papers and overseeing the refereeing process.
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