Routing Optimization with Vehicle–Customer Coordination

Wei Zhang (), Alexandre Jacquillat (), Kai Wang () and Shuaian Wang ()
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Wei Zhang: School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China; Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hong Kong SAR, China
Alexandre Jacquillat: Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142
Kai Wang: School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China
Shuaian Wang: Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hong Kong SAR, China

Management Science, 2023, vol. 69, issue 11, 6876-6897

Abstract: In several transportation systems, vehicles can choose where to meet customers rather than stopping in fixed locations. This added flexibility, however, requires coordination between vehicles and customers that adds complexity to routing operations. This paper develops scalable algorithms to optimize these operations. First, we solve the one-stop subproblem in the ℓ 1 space and the ℓ 2 space by leveraging the geometric structure of operations. Second, to solve a multistop problem, we embed the single-stop optimization into a tailored coordinate descent scheme, which we prove converges to a global optimum. Third, we develop a new algorithm for dial-a-ride problems based on a subpath-based time–space network optimization combining set partitioning and time–space principles. Finally, we propose an online routing algorithm to support real-world ride-sharing operations with vehicle–customer coordination. Computational results show that our algorithm outperforms state-of-the-art benchmarks, yielding far superior solutions in shorter computational times and can support real-time operations in very large-scale systems. From a practical standpoint, most of the benefits of vehicle–customer coordination stem from comprehensively reoptimizing “upstream” operations as opposed to merely adjusting “downstream” stopping locations. Ultimately, vehicle–customer coordination provides win–win–win outcomes: higher profits, better customer service, and smaller environmental footprint.

Keywords: vehicle–customer coordination; vehicle routing; ride-sharing; time–space network (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:69:y:2023:i:11:p:6876-6897

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