Local performance of the (1+1)-ES in a noisy environment
Local performance of the (1+1)-ES in a noisy environment
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DOI：
10.1023/a:1015059928466
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发表时间：
2002-02-01
影响因子：
14.3
通讯作者：
Beyer, HG
中科院分区：
文献类型：
--
作者：
Arnold, DV;Beyer, HG
虽然噪声是一种存在于许多现实世界的优化问题中的现象，但对它对进化算法性能的潜在影响的理解仍然是不完整的。本文研究了在无限维搜索空间的极限下，二次球面上具有各向同性正态突变的（1 + 1）-ES的适应度比例高斯噪声的影响。实验表明，结果提供了一个很好的近似有限的空间维数。结果表明，由于未能重新评估父母的健身高估导致成功概率降低和性能提高。突变强度的适应规则的影响进行了讨论，并计算出最佳的rescretrates。
While noise is a phenomenon present in many real-world optimization problems, the understanding of its potential effects on the performance of evolutionary algorithms is still incomplete. This paper investigates the effects of fitness proportionate Gaussian noise for a (1 + 1)-ES with isotropic normal mutations on the quadratic sphere in the limit of infinite search-space dimensionality. It is demonstrated experimentally that the results provide a good approximation for finite space dimensionality. It is shown that overvaluation as a result of failure to reevaluate parental fitness leads to both reduced success probabilities and improved performance. Implications for mutation strength adaptation rules are discussed and optimal resampling rates are computed.