rECGA中基于高斯PDF的因子分解性能分析

Minqiang Li, D. Goldberg, K. Sastry, Tian-Li Yu
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引用次数: 0

摘要

本文对实编码ECGA (rECGA)中基于高斯概率密度函数的单变量和多变量实值欺骗函数(URDF和MRDFi)分解的总体大小和抽样问题进行了多方面的分析。统计地描述了单高斯pdf和混合高斯pdf下rECGA的动力学特性。实验结果表明,混合高斯pdf的rECGA在MRDFi上具有次二次多项式的可扩展性,表明该算法适用于大规模可分解优化问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance Analyses of Factorization Based on Gaussian PDF In rECGA
In this paper, facet analyses are made about the population sizing and sampling of the factorization based on Gaussian probability density function in the real- coded ECGA (rECGA) on the univariate and multivariate real-valued deceptive functions (URDF and MRDFi). The dynamics of the rECGA with single Gaussian pdf and mixture Gaussian pdf are described statistically. Experimental results illustrate that the rECGA with mixture Gaussian pdf has a scalability of sub-quadratic polynomial on the MRDFi, which indicates that it is applicable to large-scale decomposable optimization problems.
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