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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The introduction of simulating annealing algorithm solves the difficulty in combination optimization effectively.

引入模拟退火算法后，有效地解决了这一组合优化的难题。

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Taking optimization design of adjustor as an example, the process of constructing object function, defining initial value and simulating dynamic system was discussed.

并以调节器参数最优化设计为例，论述了目标函数构造、初值确定、 动态系统仿真分析的过程。

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