Application of a New Improved Ant-Algorithm in TSP

Abstract:

Firstly, this paper introduces the ant colony algorithm and its principle, model and the process to realize, meanwhile, it analyses the reasons for the premature stagnation phenomenon of ant colony algorithm. Secondly, refresh and local optimal search strategy on the optimal, worst pheromone will be introduced here based on the original algorithm, as well as two line equations to avoid crossing paths, in order to expand the scope of the feasible solutions, avoid premature stagnation, and accelerate the speed of convergence. Finally, with eil51 of TSP to be an example of simulation calculation, the result shows the superiority of the improved ant colony algorithm.

• Periodical: Applied Mechanics and Materials (Volumes 291-294)
• Pages: 2905-2908
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.291-294.2905
• Online since: February 2013
• Authors: Chen Bing Li, Hua Fei Jia, Wei Dong Chen, Yu Wen Jia
• Keywords: Ant Colony Algorithm (ACA), Pheromone, Route, TSP

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