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：
10.1109/4235.985690
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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
虽然噪声是许多现实世界优化问题中存在的一种现象，但对其对进化算法性能的潜在影响的理解仍然不完整。本文研究了具有各向同性法线突变的(1+1)-ES在无限搜索空间维极限下对二次球面的适应度比例高斯噪声的影响。实验结果表明，该结果对有限空间维度有较好的逼近效果。研究表明，由于未能重新评估父母的适合度而导致的高估导致了成功概率的降低和绩效的提高。讨论了突变强度适应规则的含义，并计算了最优重采样率。
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.