有限总体模型下分布估计算法的分析

Third International Conference on Natural Computation (ICNC 2007) Pub Date : 2007-08-24 DOI:10.1109/ICNC.2007.174

Yan Wu, Yuping Wang, Xiaoxiong Liu

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引用次数: 2

摘要

本文分析了有限种群分布估计算法的收敛性。首先，通过在亲本种群的期望分布中加入误差来设计有限种群的eda模型。然后在有限种群条件下证明了三种常用的选择方案的收敛性。结果表明，eda收敛于本文所描述的误差范围内的最优解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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An Analysis of Estimation of Distribution Algorithms with Finite Population Models

The convergence of estimation of distribution algorithms (EDAs) with finite population is analyzed in this paper. At first, the models of EDAs with finite population are designed by incorporating an error into expected distribution of parent population. Then the convergence of the EDAs is proved with finite population under three widely used selection schemes. The results show that EDAs converge to the optimal solutions within the range of error described in this paper.

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Third International Conference on Natural Computation (ICNC 2007)

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