基于测试函数基准的遗传算法参数化研究

2023 3rd International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET) Pub Date : 2023-05-18 DOI:10.1109/IRASET57153.2023.10152983

E. Asmae, Hafidi Sanae, Benhala Bachir

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引用次数: 0

摘要

本文研究了适当地参数化遗传算法，以提高遗传算法的性能。参数化是解决问题之前的关键阶段。分析了遗传算法的主要参数对解质量的影响。所考虑的参数有种群大小、选择类型、交叉类型和突变率。一组数学函数(单峰和多峰)，其全局最小值是事先已知的。

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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A Study of Genetic Algorithm Parameterization via a Benchmark of Test Functions

This paper presents a study to properly parameterize the Genetic Algorithm (GA) in a way to increase its performance. Parameterization is a crucial phase before any use for problem solving. An analysis of the influence of the main parameters of GA on the quality of solutions found has been shown. The parameters taken into consideration are the population size, the type of selection, the type of crossover and the mutation rate. A set of mathematical functions (unimodal and multimodal) whose global minimum is known in advance is used for this purpose.

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2023 3rd International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET)

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