Solving geometric TSP with ants

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. Categories and Subject Descriptors I.2.8 [Artificial Intelligence]: Problem Solving, Control Methods, and Search—Heuristic methods General Terms Design, Algorithms Keywords Traveling Salesman Problem, Ant System

• Type: Conference
• Year: 2005
• Where: GECCO
• Authors: Thang Nguyen Bui, Mufit Colpan
• Keywords: Algorithms, Euclidean TSP, GECCO 2005, Traveling Salesman Problem