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http://dx.doi.org/10.9708/jksci.2011.16.3.203

Ant Colony System for solving the traveling Salesman Problem Considering the Overlapping Edge of Global Best Path  

Lee, Seung-Gwan (The College of Liberal Arts, Kyung Hee University)
Kang, Myung-Ju (Dept. of Computer Game, ChungKang College of Cultural Industries)
Publication Information
Journal of the Korea Society of Computer and Information / v.16, no.3, 2011 , pp. 203-210 More about this Journal
Abstract
Ant Colony System is a new meta heuristics algorithms to solve hard combinatorial optimization problems. It is a population based approach that uses exploitation of positive feedback as well as greedy search. It was first proposed for tackling the well known Traveling Salesman Problem. In this paper, we propose the searching method to consider the overlapping edge of the global best path of the previous and the current. This method is that we first determine the overlapping edge of the global best path of the previous and the current will be configured likely the optimal path. And, to enhance the pheromone for the overlapping edges increases the probability that the optimal path is configured. Finally, the performance of Best and Average-Best of proposed algorithm outperforms ACS-3-opt, ACS-Subpath and ACS-Iter algorithms.
Keywords
Ant Colony System; Traveling Salesman Problem; Optimization; Meta Heuristic;
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Times Cited By KSCI : 3  (Citation Analysis)
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