An improved rotationally invariant PSO: A modified standard PSO-2011
An improved rotationally invariant PSO: A modified standard PSO-2011
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DOI：
10.1109/cec.2016.7744012
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发表时间：
2016-07
期刊：
影响因子：
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通讯作者：
Yosuke Hariya;T. Shindo;K. Jin'no
中科院分区：
文献类型：
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作者：
Yosuke Hariya;T. Shindo;K. Jin'no
粒子群优化（PSO）是一种基于随机种群的算法，是为实参数优化问题而设计的。粒子群优化算法是一种简单而强大的算法，被应用于许多真实的世界问题。然而，由于在传统的粒子群算法的搜索区域存在偏差，搜索性能恶化，在不可分离的问题。为了克服这个问题，提出了标准粒子群优化2011（SPSO2011）。SPSO 2011的性能不受变量间依赖关系的影响。在这篇文章中，我们澄清了SPSO2011的性能受到搜索范围中心分布的影响。此外，我们澄清了全局搜索能力逐渐消失的中心的更新规则。因此，我们提出了一种新的更新规则，以提高全局搜索能力。通过使用CEC2005基准函数的数值实验，验证了该方法的有效性。
Particle swarm optimization (PSO) is a stochastic population-based algorithm that is designed for real-parameter optimization problems. PSO is simple and powerful algorithm, and is applied to many real world problems. However, because the bias of the search area exists in the conventional PSO, the search performance is deteriorated in non-separable problems. In order to overcome this problem, standard particle swarm optimization 2011 (SPSO2011) was proposed. The performance of SPSO2011 is not affected by the dependencies among variables. In this article, we clarify that SPSO2011 performance is affected by the distribution of the center of the search range. Also, we clarify that the global search ability fades away by the update rule of the center. Therefore, we propose a novel update rule to improve the global search ability. We clarify the effectiveness of the proposed method by numerical experiments by using CEC2005 benchmark functions.