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首页> 外文会议>International Workshop on Foundations of Genetic Algorithms(FOGA 2005); 20050105-09; Aizu-Wakamatsu City(JP) >On the Prediction of the Solution Quality in Noisy Optimization
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On the Prediction of the Solution Quality in Noisy Optimization

机译：噪声优化中解决方案质量的预测

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摘要

Noise is a common problem encountered in real-world optimization. Although it is folklore that evolution strategies perform well in the presence of noise, even their performance is degraded. One effect on which we will focus, in this paper is the reaching of a steady state that deviates from the actual optimal solution. The quality gain is a local progress measure, describing the expected one-generation change of the fitness of the population. It can be used to derive evolution criteria and steady state conditions which can be utilized as a starting point to determine the final fitness error, i.e. the expected difference between the actual optimal fitness value and that of the steady state. We will demonstrate the approach by determining the final solution quality for two fitness functions.
机译：噪声是实际优化中遇到的常见问题。尽管民间传说认为进化策略在存在噪声的情况下表现良好，但其性能也会下降。在本文中，我们将重点关注的一个影响是达到偏离实际最优解的稳态。质量提高是一项当地的进步衡量标准，描述了人口适应度的预期的一代人变化。它可以用来推导演化标准和稳态条件，这些条件可以用作确定最终适应度误差的起点，即最终的最佳适应度值与稳态适应度之间的期望差值。我们将通过确定两个适应度函数的最终解决方案质量来演示该方法。

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