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tinyos 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-The tinyos ant colony algorithm (ant colony optimization, ACO), also known as ant algorithm the the probability type algorithm is a method for finding the optimal path in the graph. By Marco Dorigo in his doctoral thesis in 1992, inspired by the behavior of ants found in the process of looking for food path. Ant colony algorithm is a simulated evolutionary algorithm, preliminary studies show that the algorithm has many excellent properties for the PID controller parameters to optimize the design problem, the design of ant colony algorithm and genetic algorithm design compared with numerical simulation results The results show that the ant colony algorithm with a new simulated evolutionary optimization method effectiveness and value
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路径优化蚁群算法matlab程序‘ 在求解该问题的蚂蚁算法中,每只蚂蚁是一个独立的用于构造路线的过程,若干蚂蚁过程之间通过自适应的信息素值来交换信息,合作求解,并不断优化。(Path optimization, ant colony algorithm, matlab program. In the ant algorithm for solving this problem, each ant is an independent procedure for constructing the route, between a number of ants by adaptive pheromone to exchange information, cooperate to solve and optimize.)
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