Ant Colony Algorithm Dynamically Adjust the Parameters Based on Chaos Theory

Abstract:

Ant colony algorithm as an intelligent bionic optimization algorithm, Because of its use of positive feedback mechanism, the result will be prone to premature, stagnation and slow speed of solving the problem etc. For this shortcoming is proposed based on chaos theory adaptive dynamic parameters ant colony algorithm (PDSACA Dynamic Parameters Self-adaptive Ant Colony Algorithm).In the process of the dynamic algorithm solving, introducing chaotic disturbance technique, the parameters of the algorithm design of dynamic changes to affect the algorithm quality and global parameters are adjusted adaptively to improve the global search capability. By using the TSPLABs reference example to test the algorithm. Experimental results show that the convergence of the algorithm, robustness and efficiency have been improved to Compare with the basic ant colony algorithm.

• Periodical: Applied Mechanics and Materials (Volumes 513-517)
• Pages: 1787-1792
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.513-517.1787
• Online since: February 2014
• Authors: Tao Gui*, Xue Liang Fu, Gai Fang Dong, Xun Ying Sun, Li Min Bao
• Keywords: Ant Colony Algorithm, Chaos Theory, Off-Line Parameter Turning

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