Title: The load-dependent electric vehicle routing problem with time windows

Authors: Zhiguo Wu; Jiepeng Wang; Chen Chen; Yunhui Liu

Addresses: College of Urban Rail Transit and Logistics, Beijing Union University, Beijing, 100101, China ' School of Economics and Management, Beihang University, Beijing, 100191, China ' Technology Center, Nanjing CRRC Logistics Service Co., Ltd., Nanjing, 210031, China ' School of Economics and Management, Tsinghua University, Beijing, 100084, China

Abstract: In recent years, many firms use electric vehicles to distribute goods. For electric vehicles, energy consumption depends on the joint effect of load and distance. In this paper, we study the electric vehicle routing problem considering the load factor, in which energy consumption is influenced by the load. We model this problem as a mixed integer linear programming and propose an adaptive large neighbourhood search to address the problem. We adopt tailored operators based on the structure of the problem. We conduct numerical experiments to evaluate the performance of the proposed algorithm. Results of numerical experiments show that: 1) a solution without considering the load factor may be infeasible when considering the load factor; 2) a solution with the shortest distance is not necessary the energy-efficient one. Moreover, we solve a practical example based on JD.com and discuss the impacts of the load factor on route policy.

Keywords: electric vehicles; load-dependent; time windows; adaptive large neighbourhood search; ALNS; heuristic algorithm.

DOI: 10.1504/IJSTL.2023.132674

International Journal of Shipping and Transport Logistics, 2023 Vol.17 No.1/2, pp.182 - 213

Received: 17 Jul 2021
Accepted: 13 Jun 2022
Published online: 07 Aug 2023 *

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