中文说明：蚁群算法(ant colony optimization, ACO)，又称蚂蚁算法，是一种用来在图中寻找优化路径的机率型算法。它由Marco Dorigo于1992年在他的博士论文中提出，其灵感来源于蚂蚁在寻找食物过程中发现路径的行为。蚁群算法是一种模拟进化算法，初步的研究表明该算法具有许多优良的性质。针对PID控制器参数优化设计问题，将蚁群算法设计的结果与遗传算法设计的结果进行了比较，数值仿真结果表明，蚁群算法具有一种新的模拟进化优化方法的有效性和应用价值。
English Description：
Ant colony algorithm (ant colony optimization, ACO), also known as ant algorithm is an algorithm used to find the optimal path probability model in the figure. It is in his doctoral thesis proposed by Marco Dorigo in 1992, inspired by the behavior of the path of the ants found in the process of looking for food. Ant colony algorithm is a simulated evolutionary algorithm, preliminary studies show that the algorithm has many excellent properties. PID controller parameters are optimized for the design, and the result will be the result of ant colony algorithm and genetic algorithm are compared, the numerical simulation results show that ant colony algorithm is a new kind of simulated evolutionary optimization method validity and application value.