高概率突变遗传算法中的种群分布动力学

2019 21st International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2019-09-01 DOI:10.1109/SYNASC49474.2019.00031

Nicolae-Eugen Croitoru

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引用次数: 2

摘要

本文研究了由非常高的突变算子概率(≈0.95)引起的遗传种群动态。受一致性序列图和分布估计算法的启发，计算了连续代之间的种群分布natϊve变化。该度量用于描述简单遗传算法的多个参数变体，对比低概率和高概率突变，以及低熵和高熵突变。

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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Population Distribution Dynamics in Genetic Algorithms with High-Probability Mutation

This paper contains an investigation into the GA population dynamics induced by very high mutation operator probabilities (≈ 0.95). Drawing inspiration from Consensus Sequence Plots and Estimation of Distribution Algorithms, population distribution natϊve changes are computed between successive generations. This metric is used to characterise multiple parameter variants for a Simple Genetic Algorithm, contrasting low-and high-probability mutation, and low-and high-entropy mutation.

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2019 21st International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)

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