The ant colony optimization algorithm is a novel simulated evolution algorithm featuring a robust global searching ability.
蚁群算法是一种模拟进化算法，具有很强的全局搜索能力。
This can greatly strengthen the cooperation between ants, accelerate the convergence speed and enhance the global searching ability.
这大大增强了蚂蚁间的合作性，加快了蚁群算法的收敛速度，提高了全局搜索能力。
The algorithm's global searching ability is improved through Cauchy variation, and local searching ability is improved by Gauss variation.
通过柯西变异，提高算法的全局搜索能力，通过高斯变异，提高算法的局部搜索能力。
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