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 Description: Swarm optimization, also known as PSO (Particle Swarm Optimization), abbreviated as PSO, in recent years, one J. Kennedy and RC Eberhart et al. [1] developed a new evolutionary algorithm (Evolutionary Algorithm- EA). One of PSO algorithm and simulated annealing algorithm is similar to evolutionary algorithms, it is also a departure random solutions, through iterative find the optimal solution, it is also uated by the fitness of the solution quality, but it' s simpler than genetic algorithm rules it is no genetic algorithm " cross" (crossover) and " variation" (mutation) operation, follow it through to the current search to find the optimal value of the global optimum. This algorithm is its easy implementation, high precision, rapid convergence, etc. attracted academic attention, and demonstrated its superiority in solving practical problems. Particle swarm algorithm is a parallel algorithm.
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粒子群算法求解多元函数极值\fitness.m
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粒子群算法求解多元函数极值
    

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