Modeling and evolutionary optimization for multi-objective vehicle routing problem with real-time traffic conditions

Date

2020-02

Advisors

Journal Title

Journal ISSN

ISSN

Volume Title

Publisher

Association for Computing Machinery

Type

Conference

Peer reviewed

Yes

Abstract

The study of the vehicle routing problem (VRP) is of outstanding significance for reducing logistics costs. Currently, there is little VRP considering real-time traffic conditions. In this paper, we propose a more realistic and challenging multi-objective VRP containing real-time traffic conditions. Besides, we also offer an adaptive local search algorithm combined with a dynamic constrained multi-objective evolutionary framework. In the algorithm, we design eight local search operators and select them adaptively to optimize the initial solutions. Experimental results show that our algorithm can obtain an excellent solution that satisfies the constraints of the vehicle routing problem with real-time traffic conditions.

Description

Keywords

Vehicle routing problem, Local search, Multi-objective optimization, Constrained optimization

Citation

Xiao, L., Li, C., Wang, J., Mavrovouniotis, M., Yang, S. and Dan, X. (2020) Modeling and evolutionary optimization for multi-objective vehicle routing problem with real-time traffic conditions. Proceedings of the 12th International Conference on Machine Learning and Computing, pp. 518-523

Rights

Research Institute

Institute of Artificial Intelligence (IAI)