An Improved Ant Colony Approach for the Competitive Traveling Salesmen Problem

Du, Xinyang; Bai, Ruibin; Cui, Tianxiang; Qu, Rong; Li, Jiawei

Abstract

A competitive traveling salesmen problem is a variant of traveling salesman problem in that multiple agents compete with each other in visiting a number of cities. The agent who is the first one to visit a city will receive a reward. Each agent aims to collect as more rewards as possible with the minimum traveling distance. There is still not effective algorithms for this complicated decision making problem. We investigate an improved ant colony approach for the competitive traveling sales-men problem which adopts a time dominance mechanism and a revised pheromone depositing method to improve the quality of solutions with less computational complexity. Simulation results show that the proposed algorithm outperforms the state of art algorithms.

Citation

Du, X., Bai, R., Cui, T., Qu, R., & Li, J. (2022, July). An Improved Ant Colony Approach for the Competitive Traveling Salesmen Problem. Presented at 2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings, Padua, Italy

• Presentation Conference Type: Edited Proceedings
• Conference Name: 2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings
• Start Date: Jul 18, 2022
• End Date: Jul 23, 2022
• Acceptance Date: Jun 22, 2023
• Online Publication Date: Sep 6, 2022
• Publication Date: Jul 18, 2022
• Deposit Date: Sep 2, 2023
• Publicly Available Date: Jul 19, 2024
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Pages: 40-44
• Book Title: 2022 IEEE Congress on Evolutionary Computation (CEC)
• ISBN: 978-1-6654-6709-4
• DOI: https://doi.org/10.1109/cec55065.2022.9870414
• Public URL: https://nottingham-repository.worktribe.com/output/11462419
• Publisher URL: https://ieeexplore.ieee.org/document/9870414