存在多个全局最优的粒子群算法

Sunny Choi, B. Mayfield
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引用次数: 1

摘要

典型粒子群优化(PSO)的动态分析表明,当参数值phi_max = 4.1和收缩系数chi = 0.729时,能提供充分的探测和防止群体爆炸。通过实例表明,在某些情况下,这些值并不能防止群爆。另一个例子表明,即使在群不爆炸的情况下,具有这些参数值的规范粒子群优化算法仍然不能无限收敛。对粒子群的令人满意的分析尚未完成,而且需要放弃某些过分简化粒子行为的假设。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Particle swarm optimization in the presence of multiple global optima
Dynamic analyses of canonical particle swarm optimization (PSO) have indicated that parameter values of phi_max = 4.1 and constriction coefficient chi = 0.729 provide adequate exploration and prevent swarm explosion. This paper shows by example that these values do not prevent swarm explosion in some cases. In other examples it is shown that even when the swarm does not explode, the canonical PSO algorithm with these parameter values can still fail to converge indefinitely. A satisfactory analysis of PSO has yet to be made, and will require abandoning certain assumptions that oversimplify particle behavior.
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