Ant Colony optimization (ACO) is a new-style simulating evolution algorithm. The behavior of real ant colonies foraging for food is simulated and used for solving optimization problems.

蚁群算法是一种新型的模拟进化算法，它通过模拟蚁群在觅食过程中寻找最短路径的方法来求解优化问题。

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Global path planning problem for autonomous underwater vehicle (AUV) based on large-scale chart data is investigated by using ant colony optimization (in shorts, ACO) algorithm.

在大范围海洋环境中，应用蚁群算法对自主式水下潜器(AUV)的全局路径规划问题进行了研究。

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Two improvements on Ant Colony Optimization(ACO) algorithm is presented in this paper.

蚁群算法在处理大规模优化问题时效率很低。

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