Solving geometric TSP with ants

Thang N. Bui, Mufit Colpan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations


This paper presents an ant-based approach for solving the Traveling Salesman Problem (TSP). Novel concepts of this algorithm that distinguish it from the other heuristics are the inclusion of a preprocessing stage and the use of a modified version of an ant-based approach with local optimization in multi stages. Experimental results show that this algorithm outperforms ACS [1] and is comparable to MMAS [4] for Euclidean TSP instances. Of the 40 instances of Euclidean TSP from TSPLIB [5] that were tested, this algorithm found the optimal solution for 37 instances. For the remaining instances, this algorithm returned solutions that were within 0.3% of the optimum.

Original languageEnglish (US)
Title of host publicationGECCO 2005 - Genetic and Evolutionary Computation Conference
EditorsH.G. Beyer, U.M. O'Reilly, D. Arnold, W. Banzhaf, C. Blum, E.W. Bonabeau, E. Cantu-Paz, D. Dasgupta, K. Deb, al et al
Number of pages2
StatePublished - 2005
EventGECCO 2005 - Genetic and Evolutionary Computation Conference - Washington, D.C., United States
Duration: Jun 25 2005Jun 29 2005

Publication series

NameGECCO 2005 - Genetic and Evolutionary Computation Conference


OtherGECCO 2005 - Genetic and Evolutionary Computation Conference
Country/TerritoryUnited States
CityWashington, D.C.

All Science Journal Classification (ASJC) codes

  • General Engineering


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