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http://dx.doi.org/10.5392/JKCA.2011.11.3.100

Balance between Intensification and Diversification in Ant Colony Optimization  

Lee, Seung-Gwan (경희대학교 후마니타스칼리지)
Choi, Jin-Hyuk (경희대학교 후마니타스칼리지)
Publication Information
The Journal of the Korea Contents Association / v.11, no.3, 2011 , pp. 100-107 More about this Journal
Abstract
One of the important fields for heuristic algorithm is how to balance between Intensification and Diversification. In this paper, we deal with the performance improvement techniques through balance the intensification and diversification in Ant Colony System(ACS) which is one of Ant Colony Optimization(ACO). In this paper, we propose the hybrid searching method between intensification strategy and diversification strategy. First, the length of the global optimal path does not improved within the limited iterations, we evaluates this state that fall into the local optimum and selects the next node using changed parameters in the state transition rule. And then we consider the overlapping edge of the global best path of the previous and the current, 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, ACS-Iter and ACS-Global-Ovelap algorithms.
Keywords
Ant Colony System; Ant Colony Optimozation; Traveling Salesman Problem; Optimization; Heuristic; Intensification; Diversification;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
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1 M. Dorigo, M. Birattari, and T. Stutzle, "Ant Colony Optimization - Artificial Ants as a Computational Intelligence Technique," IEEE Computational Intelligence Magazine, Vol.1, No.4, pp.28-39, 2006.   DOI
2 http://elib.zib.de/pub/Packages/mp-testdata/tsp/tsplib/tsplib.html
3 I. K. Kim and M. Y. Youn, "Improved Ant Colony System for the Traveling Salesman Problem," The KIPS transactions. Part B, Vol.12, No.7, pp.823-828, 2005.   과학기술학회마을   DOI   ScienceOn
4 S. G. Lee, "Ant Colony System Considering the Iteration Search Frequency that the Global Optimal Path does not Improved," Journal of The Korea Society of Computer and Information, Vol.14, No.1, pp.9-15, 2009.   과학기술학회마을
5 M. Randall and E. Tonkes, "Intensification and diversification strategies in ant colony system," Complexity International, Vol.9, 2002.
6 R. Sun, S. Tatsumi and G. Zhao, "Multiagent reinforcement learning method with an improved ant colony system," 2001 IEEE International Conference Systems, Man, and Cybernetics, pp.1612-1617, 2001.   DOI
7 S. G Lee and T. C Chung, "Performance Improvement of Cooperating Agents through Balance between Intensification and Diversification," The IEEK journals : CI, Vol.40, No.6, pp.87-94, 2003.   과학기술학회마을
8 S. G Lee, T. U Jung and T. C Chung, "Improved Ant Agents System by the Dynamic Parameter Decision," Proceedings of IEEE International Conference on FUZZ-IEEE 2001, pp.666-669, 2001   DOI
9 S. G Lee and T. C Chung, "A Study about Additional Reinforcement in Local Updating and Global Updating for Efficient Path Search in Ant Colony System," The KIPS Transactions : Part B, pp.237-242, 2003.   과학기술학회마을   DOI   ScienceOn
10 L. M. Gambardella and M. Dorigo, "Ant Colony System: A Cooperative Learning approach to the Traveling Salesman Problem," IEEE Transactions on Evolutionary Computation, Vol.1, No.1, pp.53-66, 1997.   DOI
11 M. Dorigo, L. M. Gambardella, M. Middendorf and T. Stutzle, "Ant Colony Optimization," IEEE Transactions on Evolutionary Computation, Vol.6, No.4, 2002.
12 M. Dorigo and C. Blum. "Ant colony optimization theory: A survey," Theoretical Computer Science, 344(2-3), pp.243-278, 2005.   DOI   ScienceOn
13 S. G. Lee and M. J. Kang, "Ant Colony System for solving the traveling Salesman Problem Considering the Overlapping Edge of Global Best Path," Journal of The Korea Society of Computer and Information, Vol.16, No.3, 2011. In press.