Niching with Sub-swarm Based Particle Swarm Optimization

M. Rashid, A. R. Baig, K. Zafar
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引用次数: 5

Abstract

In this study we present a sub-swarm based particle swarm optimization algorithm for niching (NSPSO). The NSPSO algorithm is capable of locating and maintaining a sufficient number of niches throughout the execution of the algorithm. The niches which are identified are then exploited by using a sub-swarm strategy which tries to refine the niche and converge to an optimum solution. NSPSO is capable of locating multiple solutions and is well suited for multimodal optimization problems. From the experimentation results, we have observed that NSPSO is quite efficient in locating both global and local optima. We present a comparison of the performance of NSPSO with NichePSO and SPSO.
基于子群的小生境粒子群优化
本文提出了一种基于子群的粒子群定位优化算法(NSPSO)。NSPSO算法能够在整个算法执行过程中定位和维护足够数量的小生境。然后使用子群策略对确定的生态位进行开发,该策略试图细化生态位并收敛到最优解。NSPSO能够定位多个解,非常适合于多模态优化问题。实验结果表明,NSPSO在全局最优点和局部最优点的定位上都是非常有效的。我们将NSPSO与NichePSO和SPSO的性能进行了比较。
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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