Synchronized Deliveries with a Bike and a Self-Driving Robot

IF 4.4 2区工程技术 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

Transportation Science Pub Date : 2023-12-08 DOI:10.1287/trsc.2023.0169

Yanlu Zhao, Diego Cattaruzza, Ningxuan Kang, Roberto Roberti

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引用次数: 0

Abstract

Online e-commerce giants are continuously investigating innovative ways to improve their practices in last-mile deliveries. Inspired by the current practices at JD.com (the largest online retailer by revenue in China), we investigate a delivery problem that we call the traveling salesman problem with bike and robot (TSPBR), where a cargo bike is aided by a self-driving robot to deliver parcels to customers in urban areas. We present two mixed-integer linear programming models and describe a set of valid inequalities to strengthen their linear relaxation. We show that these models can yield optimal solutions of TSPBR instances with up to 60 nodes. To efficiently find heuristic solutions, we also present a genetic algorithm based on a dynamic programming recursion that efficiently explores large neighborhoods. We computationally assess this genetic algorithm on instances provided by JD.com and show that high-quality solutions can be found in a few minutes of computing time. Finally, we provide some managerial insights to assess the impact of deploying the bike-and-robot tandem to deliver parcels in the TSPBR setting.

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用自行车和自动驾驶机器人同步送货

在线电子商务巨头正在不断研究创新方法，以改善他们在最后一英里配送方面的做法。受京东(中国收入最大的在线零售商)当前做法的启发，我们研究了一个配送问题，我们称之为自行车和机器人的旅行推销员问题(TSPBR)，在这个问题上，一辆货运自行车由一个自动驾驶机器人辅助，向城市地区的客户运送包裹。我们提出了两个混合整数线性规划模型，并描述了一组有效的不等式来加强它们的线性松弛性。我们证明这些模型可以产生最多60个节点的TSPBR实例的最优解。为了有效地找到启发式解决方案，我们还提出了一种基于动态规划递归的遗传算法，该算法可以有效地探索大邻域。我们在京东提供的实例上对这种遗传算法进行了计算评估，并表明可以在几分钟的计算时间内找到高质量的解决方案。最后，我们提供了一些管理见解，以评估在TSPBR设置中部署自行车和机器人串联递送包裹的影响。

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

Transportation Science 工程技术-运筹学与管理科学

CiteScore

8.30

自引率

10.90%

发文量

111

审稿时长

12 months

期刊介绍： Transportation Science, published quarterly by INFORMS, is the flagship journal of the Transportation Science and Logistics Society of INFORMS. As the foremost scientific journal in the cross-disciplinary operational research field of transportation analysis, Transportation Science publishes high-quality original contributions and surveys on phenomena associated with all modes of transportation, present and prospective, including mainly all levels of planning, design, economic, operational, and social aspects. Transportation Science focuses primarily on fundamental theories, coupled with observational and experimental studies of transportation and logistics phenomena and processes, mathematical models, advanced methodologies and novel applications in transportation and logistics systems analysis, planning and design. The journal covers a broad range of topics that include vehicular and human traffic flow theories, models and their application to traffic operations and management, strategic, tactical, and operational planning of transportation and logistics systems; performance analysis methods and system design and optimization; theories and analysis methods for network and spatial activity interaction, equilibrium and dynamics; economics of transportation system supply and evaluation; methodologies for analysis of transportation user behavior and the demand for transportation and logistics services. Transportation Science is international in scope, with editors from nations around the globe. The editorial board reflects the diverse interdisciplinary interests of the transportation science and logistics community, with members that hold primary affiliations in engineering (civil, industrial, and aeronautical), physics, economics, applied mathematics, and business.