An Improved Ant Colony Approach for the Competitive Traveling Salesmen Problem

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

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publication2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665467087
DOIs
Publication statusPublished - 2022
Event2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Padua, Italy
Duration: 18 Jul 202223 Jul 2022

Publication series

Name2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings

Conference

Conference2022 IEEE Congress on Evolutionary Computation, CEC 2022
Country/TerritoryItaly
CityPadua
Period18/07/2223/07/22

Keywords

  • algorithm
  • Ant colony
  • competitive traveling salesmen problem
  • heuristic

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computational Mathematics
  • Control and Optimization

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