一种自适应最大最小蚁群算法

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Abstract The structure and principle of ant colony algorithm are introduced. Its excellence and deficiency are analyzed, and several important improved models are reviewed. Based on MaxMin Ant Systems (MMAS), an adaptive improved model is put forward. To achieve adaptive adjustment of parameters and enhance the performance of the proposed algorithm, the weighting coefficient, state transferring rule and pheromone increment mode are improved. To testify the performance of the improved algorithm, numerical experiment is made and the result shows the improved algorithm is effective.

Key words： Ant Colony Algorithm MaxMin Ant System (MMAS) Adaptive Traveling Salesman Problem

Received: 30 May 2006

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TP301.6

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	SU Chang
	TU Jun

Cite this article:

SU Chang,TU Jun. An Adaptive MaxMin Ant Colony Algorithm[J]. , 2007, 20(5): 688-691.

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http://manu46.magtech.com.cn/Jweb_prai/EN/ OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2007/V20/I5/688

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