用快速收敛粒子群优化算法解决函数优化问题
Functions optimization based on fast convergence particle swarm optimization
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摘要: 针对标准PSO算法在计算过程中易陷入局部最优而无法跳出的问题,提出了一种基于平衡单个粒子位置多样性的快速收敛PSO(FCPSO)算法.该算法在PSO算法中引入一个新的参数,即粒子平均尺寸以快速准确地锁定全局最优解.实验结果表明,FCPSO算法的收敛性明显优于PSO算法和CPSO算法.Abstract: Aimed at the problem that the standard PSO algorithm was very sensitive to fall into the phenomenon of local minima and couldn't escape,a new fast convergence PSO (FCPSO) algorithm based on balancing the diversity of location of individual particle was proposed. The algorithm introduced a new parameter, namely particle mean dimension was used to locate the global optimum solution fast and accurately. The experiment results showed that the convergence of the FCPSO algorithm was better than PSO algorithm and CPSO algorithm.
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