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Niching with Sub-swarm based Particle Swarm Optimization

机译:与基于群的基于粒子的粒子群优化的努力

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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.
机译:在这项研究中,我们介绍了一种基于群的粒子群群优化算法,用于抗性(NSPSO)。 NSPSO算法能够在整个算法执行过程中定位和维持足够数量的抗核电。然后通过使用分组的策略来利用所识别的核实,该策略试图将利基细化并收敛到最佳解决方案。 NSPSO能够定位多种解决方案,并且非常适合多式化优化问题。从实验结果来看,我们观察到NSPSO在定位全球和本地最优的方面非常有效。我们对NICHEPSO和SPSO的NSPSO的性能进行了比较。

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