Solving geometric TSP with ants

Authors:
Thang N. Bui;Mufit Colpan
Affiliations:
Pennsylvania State University at Harrisburg, Middletown, PA;Pennsylvania State University at Harrisburg, Middletown, PA
Venue:
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Year:
2005

Citing 2
Cited 0

Data structures for traveling salesmen

SODA '93 Selected papers from the fourth annual ACM SIAM symposium on Discrete algorithms
Ant colony system: a cooperative learning approach to the traveling salesman problem

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Abstract

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.