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中文摘要：
蚁群优化算法是一种新型的解决组合优化问题的仿真型算法，在许多领域中都已获得成功的应用，但却有容易陷入局部最优的缺陷。本文将元胞自动机思想引入到蚂蚁算法中，提出一种新的元胞蚂蚁算法，通过算法的元胞演化机制对信息素的二次分配，改善了对解空间的搜索性能，并从理论上证明了算法的渐近收敛性。
英文摘要：
Ant algorithm has successfully sol,ed series of discrete optimization problems. However its global convergence is not fully studied and proved. Cellular Ant Algorithm is a new method for optimization based on the principle of cellular automata. Through redistributing on the pheromone of the ants, the algorithm is improved on the search performance in solution space. This paper gives a convergence analysis for Cellular Ant Algorithm by using the theory of Markov Chains. It is shown that under certain conditions, the solutions generated in each iteration of this graph--based cellular ant system converge with a probability that can be made arbitrarily close to 1.
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