Particle swarm optimizer: The impact of unstable particles on performance

C. Cleghorn, A. Engelbrecht
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引用次数: 31

Abstract

There exists a wealth of theoretical analysis on particle swarm optimization (PSO), specifically the conditions needed for stable particle behavior are well studied. This paper investigates the effect that the stability of the particle has on the PSO's actually ability to optimize. It is shown empirically that a majority of PSO parameters that are theoretically unstable perform worse than a trivial random search across 28 objective functions, and across various dimensionalities. It is also noted that there exists a number of parameter configurations just outside the stable-2 region which did not exhibit poor performance, implying that a minor violation of the conditions for order-2 stability is still acceptable in terms of overall performance of the PSO.
粒子群优化器:不稳定粒子对性能的影响
关于粒子群优化(PSO)已有大量的理论分析,特别是对粒子稳定行为所需的条件进行了较好的研究。本文研究了粒子的稳定性对粒子群实际优化能力的影响。经验表明,大多数理论上不稳定的粒子群参数在28个目标函数和各种维度上的随机搜索表现不如一个平凡的随机搜索。还需要注意的是,在稳定-2区域之外存在许多参数配置,这些配置并未表现出较差的性能,这意味着就PSO的总体性能而言,轻微违反2阶稳定性条件仍然是可以接受的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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