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A niche GSA method with nearest neighbor scheme for multimodal optimization

机译:具有多模优邻方案的Niche GSA方法

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In this paper, a new niching method based on Gravitational Search Algorithm (GSA) is proposed in which species are formed within the population (swarm) based on a nearest neighbor (NN) scheme. Also, we suggest a scheme to detect the niches inside the population by using the hill valley algorithm without the need of a pairwise comparison between any pair of solutions inside the population. In order to improve the exploitation capability of the proposed niching method, the formed species are balanced such that they are forced to have almost equal number of members. This mechanism enables the species to explore more optima via diversity conservation in the swarm. Experimental results of using several multimodal benchmark functions confirm the effectiveness of the proposed niching scheme compared to well-known existing niching methods.
机译:本文提出了一种基于重力搜索算法(GSA)的新的幂位方法,其中基于最近的邻居(NN)方案在群体(SWARM)内形成。 此外,我们建议通过使用Hill Valley算法检测人群内部的努力的方案,而无需在人口内的任何一对溶液之间的成对比较。 为了提高所提出的占状法方法的开发能力,所形成的物种是平衡的,使得它们被迫具有几乎相等的成员。 这种机制使物种能够通过群体中的多样性保护来探索更多Optima。 使用几种多模式基准函数的实验结果证实了所提出的抗议方案的有效性与众所周知的现有疾病方法相比。

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