Title: Optimisation of urban distribution paths for electric logistics vehicles based on shared pre-positioning warehouse mode

Authors: Yanfeng Wu; Xueping Liu; Kai Tian

Addresses: College of Vehicle and Transportation Engineering, Henan University of Science and Technology, Luoyang, 471003, China ' College of Vehicle and Transportation Engineering, Henan University of Science and Technology, Luoyang, 471003, China ' College of Vehicle and Transportation Engineering, Henan University of Science and Technology, Luoyang, 471003, China

Abstract: To address the problems of high cost, low efficiency and load rate of urban logistics transportation, this work studies the electric vehicle routing problem. First, a novel urban logistics distribution mode, namely, the shared pre-positioning warehouse mode (SPWM) is proposed, including pick-up stage and distribution stage. Second, considering the constraints of time window, vehicle capacity, and battery capacity, the electric vehicle route optimisation models are established for the two stages of the SPWM. Third, an improved genetic algorithm by combining elite retention strategy and swap operator is proposed to solve the model. Finally, we evaluated the proposed mode on a real-world case including five suppliers and thirty customers. Compared with the path optimisation results of the traditional distribution mode (TDM), the SPWM reduces the total cost by 14.85%, the travelled mileage by 66.15%, and improved the load rate by 124.09%, which verify effectiveness of the proposed model and algorithm.

Keywords: urban logistics distribution; shared pre-positioning warehouse; electric vehicle routing problem; genetic algorithm.

DOI: 10.1504/IJADS.2025.149528

International Journal of Applied Decision Sciences, 2025 Vol.18 No.6, pp.692 - 718

Received: 19 Jan 2024
Accepted: 09 Sep 2024
Published online: 05 Nov 2025 *

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