基于车辆移动泊车为客户自提的无人机旅行商问题

IF 8.8 1区 工程技术 Q1 ECONOMICS
Lingrui Hong , Lin Zhou , Roberto Baldacci
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引用次数: 0

摘要

介绍了最后一英里配送中基于车辆移动泊车自提(TSPD-VMPCP)的无人机旅行商问题。考虑了一组顶点,包括仓库,停车位,必须在预定义的时间窗口内由卡车或无人机直接访问的送货上门(HD)客户,以及必须由指定停车位服务的自提(CP)偏好的客户。具体来说,我们允许无人机执行多回路,其中无人机在同一位置发射和降落。CP客户使用基于其自提行为和卡车停机时间的概率函数进行覆盖。TSPD-VMPCP旨在最大限度地降低总运营成本。我们将TSPD-VMPCP建模为一个混合整数线性规划,并开发了一种自适应大邻域搜索(ALNS)元启发式算法,以及基于可变邻域下降(VND)和数学的两阶段局部搜索(2P-LS)。我们通过在小实例上将ALNS与Gurobi求解器进行比较来评估其性能。中、大型实例的数值结果突出了ALNS各组成部分的有效性。此外,我们还提供了一些管理见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The traveling salesman problem with drone based on vehicle mobile parking for customer self-pickup
This paper introduces the traveling salesman problem with drone based on vehicle mobile parking for customer self-pickup (TSPD-VMPCP) in last-mile delivery. A set of vertices is considered, including a depot, parking spots, home delivery (HD) customers that must be visited directly within predefined time windows by truck or drone, and customers with self-pickup (CP) preference that must be served by designated parking spots. Specifically, we allow the drone to perform multi-loop, in which the drone launches and lands at the same location. CP customers are covered using a probability function based on their self-pickup behavior and the truck’s stoppage duration. The TSPD-VMPCP aims to minimize the total operating cost. We model the TSPD-VMPCP as a mixed-integer linear program and develop an adaptive large neighborhood search (ALNS) metaheuristic, in addition to a two-phase local search (2P-LS) based on variable neighborhood descent (VND) and matheuristic. We assess the performance of ALNS by comparing it with the Gurobi solver on small instances. The numerical results for medium and large instances highlight the effectiveness of the various components of the ALNS. Furthermore, we provide some managerial insights.
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来源期刊
CiteScore
16.20
自引率
16.00%
发文量
285
审稿时长
62 days
期刊介绍: Transportation Research Part E: Logistics and Transportation Review is a reputable journal that publishes high-quality articles covering a wide range of topics in the field of logistics and transportation research. The journal welcomes submissions on various subjects, including transport economics, transport infrastructure and investment appraisal, evaluation of public policies related to transportation, empirical and analytical studies of logistics management practices and performance, logistics and operations models, and logistics and supply chain management. Part E aims to provide informative and well-researched articles that contribute to the understanding and advancement of the field. The content of the journal is complementary to other prestigious journals in transportation research, such as Transportation Research Part A: Policy and Practice, Part B: Methodological, Part C: Emerging Technologies, Part D: Transport and Environment, and Part F: Traffic Psychology and Behaviour. Together, these journals form a comprehensive and cohesive reference for current research in transportation science.
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