Learning-based Ant Colony Optimization Algorithm for Solving a Kind of Complex 2-Echelon Vehicle Routing Problem

Authors

Xue Chen, School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, ChinaFollow
Rong Hu, School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, ChinaFollow
Hui Wang, Zhaotong Cigarette Factory, Hongta Tobacco Co. , Ltd, Zhaotong 657000, China
Zuocheng Li, School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China
Bin Qian, School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China
Yixu Li, School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China

Abstract

Abstract: Aiming at green 2-echelon vehicle routing problem with simultaneous pick-up and delivery, a learning-based ant colony optimization algorithm combined with clustering decomposition is proposed. The objective function to be minimized is total transportation cost wherein carbon emission cost is specially considered. Associated with the mutual coupling features of the 2-echelon vehicle routing problem, we propose a distance-based clustering method to decompose the original problem into a set of sub-problems. Then, a learning-based ant colony optimization algorithm is presented to find the solutions of the sub-problems based on which the solution of the original problem can be obtained. In the algorithm, we introduce a problem-dependent three-dimensional probability matrix to represent pheromone matrix, which is used to learn valuable information about high-quality solutions and improve global search ability. Thereafter, we propose a local search strategy based on the search behavior of the algorithm to learn information about excellent individuals for six dedicated neighborhood search operators, so as to enhance local search ability. Results of numerical experiments and algorithm comparisons demonstrate the effectiveness of the proposed algorithm.

Recommended Citation

Chen, Xue; Hu, Rong; Wang, Hui; Li, Zuocheng; Qian, Bin; and Li, Yixu (2023) "Learning-based Ant Colony Optimization Algorithm for Solving a Kind of Complex 2-Echelon Vehicle Routing Problem," Journal of System Simulation: Vol. 35: Iss. 11, Article 16.
DOI: 10.16182/j.issn1004731x.joss.22-0682
Available at: https://dc-china-simulation.researchcommons.org/journal/vol35/iss11/16

First Page

2476

Last Page

2495

CLC

TP391.9

Recommended Citation

Chen Xue, Hu Rong, Wang Hui, et al. Learning-based Ant Colony Optimization Algorithm for Solving a Kind of Complex 2-Echelon Vehicle Routing Problem[J]. Journal of System Simulation, 2023, 35(11): 2476-2495.

Corresponding Author

Hu Rong

DOI

10.16182/j.issn1004731x.joss.22-0682