@inproceedings{eaea3d1f440e4a4fb5b09f532e4a858f,
title = "An Improved Ant Colony Approach for the Competitive Traveling Salesmen Problem",
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.",
keywords = "Ant colony, algorithm, competitive traveling salesmen problem, heuristic",
author = "Xinyang Du and Ruibin Bai and Tianxiang Cui and Rong Qu and Jiawei Li",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE Congress on Evolutionary Computation, CEC 2022 ; Conference date: 18-07-2022 Through 23-07-2022",
year = "2022",
doi = "10.1109/CEC55065.2022.9870414",
language = "English",
series = "2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings",
address = "United States",
}