Research on Vehicle Path Optimization Algorithms for Urban Logistics and Distribution

Authors

Zhenpeng Ma, State-Province Joint Engineering and Research Center of Advanced Networking and Intelligent Information Services, School of Information Science and Technology, Northwest University, Xi'an 710127, China; Shaanxi Key Laboratory of Higher Education Institution of Generative Artificial Intelligence and Mixed Reality, Xi'an 710127, China
Hanyang Jiao, State-Province Joint Engineering and Research Center of Advanced Networking and Intelligent Information Services, School of Information Science and Technology, Northwest University, Xi'an 710127, China
Zhe Zhang, State-Province Joint Engineering and Research Center of Advanced Networking and Intelligent Information Services, School of Information Science and Technology, Northwest University, Xi'an 710127, China; Shaanxi Key Laboratory of Higher Education Institution of Generative Artificial Intelligence and Mixed Reality, Xi'an 710127, China
Cheng Liu, State-Province Joint Engineering and Research Center of Advanced Networking and Intelligent Information Services, School of Information Science and Technology, Northwest University, Xi'an 710127, China; Shaanxi Key Laboratory of Higher Education Institution of Generative Artificial Intelligence and Mixed Reality, Xi'an 710127, China
Bo Jiang, State-Province Joint Engineering and Research Center of Advanced Networking and Intelligent Information Services, School of Information Science and Technology, Northwest University, Xi'an 710127, China; Shaanxi Key Laboratory of Higher Education Institution of Generative Artificial Intelligence and Mixed Reality, Xi'an 710127, China
Lin Wang, State-Province Joint Engineering and Research Center of Advanced Networking and Intelligent Information Services, School of Information Science and Technology, Northwest University, Xi'an 710127, China; Shaanxi Key Laboratory of Higher Education Institution of Generative Artificial Intelligence and Mixed Reality, Xi'an 710127, China

Abstract

Abstract: Existing optimization algorithms for solving the vehicle routing problem with time windows (VRPTW) are prone to fall into local optimal solutions and have slow convergence speed. To address this issue, a K-means clustering algorithm and improved large neighborhood search algorithm (K-means-ILNSA) was proposed. A strategy of clustering before optimization was adopted, and the K-means algorithm was adopted to group the customers to be delivered, so as to improve the optimization efficiency. The genetic algorithm was adopted to optimize each group of customers generated by clustering separately to initially plan the distribution routes. The large neighborhood search (LNS) algorithm was introduced to further optimize the delivery routes, effectively avoiding the algorithm getting trapped in local optimal solutions. Experimental results show that the proposed algorithm can effectively solve the vehicle path problem with time windows, and the generated total distance of vehicle is short. The solving efficiency after optimization is high.

Recommended Citation

Ma, Zhenpeng; Jiao, Hanyang; Zhang, Zhe; Liu, Cheng; Jiang, Bo; and Wang, Lin (2025) "Research on Vehicle Path Optimization Algorithms for Urban Logistics and Distribution," Journal of System Simulation: Vol. 37: Iss. 11, Article 6.
DOI: 10.16182/j.issn1004731x.joss.24-0639
Available at: https://dc-china-simulation.researchcommons.org/journal/vol37/iss11/6

First Page

2768

Last Page

2777

CLC

TP391.9

Recommended Citation

Ma Zhenpeng, Jiao Hanyang, Zhang Zhe, et al. Research on Vehicle Path Optimization Algorithms for Urban Logistics and Distribution[J]. Journal of System Simulation, 2025, 37(11): 2768-2777.

Corresponding Author

Liu Cheng

DOI

10.16182/j.issn1004731x.joss.24-0639