Time-Dependent Multi-Center Semi-Open Heterogeneous Fleet Path Optimization and Charging Strategy

Tingxin Wen () and Haoting Meng
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Tingxin Wen: School of Business Administration, Liaoning Technical University, Huludao 125100, China
Haoting Meng: School of Business Administration, Liaoning Technical University, Huludao 125100, China

Mathematics, 2025, vol. 13, issue 7, 1-27

Abstract: To address the challenges of distribution cost and efficiency in electric vehicle (EV) logistics, this study proposes a time-dependent, multi-center, semi-open heterogeneous fleet model. The model incorporates a nonlinear power consumption measurement framework that accounts for vehicle parameters and road impedance, alongside an objective function designed to minimize the total cost, which includes fixed vehicle costs, driving costs, power consumption costs, and time window penalty costs. The self-organizing mapping network method is employed to initialize the EV routing, and an improved adaptive large neighborhood search (IALNS) algorithm is developed to solve the optimization problem. Experimental results demonstrate that the proposed algorithm significantly outperforms traditional methods in terms of solution quality and computational efficiency. Furthermore, through real-world case studies, the impacts of different distribution modes, fleet sizes, and charging strategies on key performance indicators are analyzed. These findings provide valuable insights for the optimization and management of EV distribution routes in logistics enterprises.

Keywords: electric vehicle path problem; improved adaptive large neighborhood search algorithm; heterogeneous fleet; time-dependent; multi-center (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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