集群重启DM:新的全局优化算法

M. Dlapa
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引用次数: 2

摘要

本文描述了具有重新启动的全局优化方法差分迁移(DM),并与重新启动协方差矩阵适应进化策略(IPOP-CMA-ES)一起进行了评价。微分迁移是SOMA(自组织迁移算法)的另一个全局优化步骤,它结合了SOMA的两种基本的个体移动方法——所有到一和所有到所有,通过聚类分析和内部算法常量定义从一种移动到另一种移动的连续变化。所提出的算法实现了差分进化的基本思想,无论它们在自然环境中的原始解释如何,随后提高了寻找全局极值的效率,这主要适用于基准测试中存在的噪声多模态成本函数以及现实世界中的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cluster restarted DM: New algorithm for global optimisation
Global optimisation method Differential Migration (DM) with restarting is described in this paper and evaluated together with Restart Covariance Matrix Adaptation Evolution Strategy With Increasing Population Size (IPOP-CMA-ES). Differential Migration is another step in global optimisation from SOMA (Self-Organizing Migration Algorithm) combining two basic individual movement methods of SOMA — all-to-one and all-to-all, via cluster analysis and internal algorithm constant defining continuous change from one type of movement to another. The proposed algorithm implements essential ideas of Differential Evolution regardless of their original interpretation in living nature with subsequent increase of efficiency in finding global extreme which holds mainly for noisy multimodal cost functions present in the benchmarks as well as in real world applications.
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