基于混沌理论的种群迁移新算法

Yuwu Lu, Xueying Liu
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引用次数: 3

摘要

为了提高种群迁移算法(PMA)的求解精度和收敛性,避免其早熟,本文将混沌理论与PMA相结合。通过将混沌理论的逻辑映射引入到PMA中,利用混沌理论的遍历性、随机性和规律性得到改进算法。实验结果表明:将混沌理论的遍历性、随机性和规律性引入到PMA中,可以有效地提高PMA的解精度和收敛性,有效地避免了早熟现象。改进后的算法性能良好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A New Population Migration Algorithm Based on the Chaos Theory
In order to improve the solution accuracy and the convergence of Population Migration Algorithm (PMA) and avoiding its prematurity, in this paper, we combined chaos theory with PMA. By introducing logistic mapping of chaos theory into PMA, we use the ergodicity, randomicity and regularity of chaos theory to attain an improved algorithm. The experimental results show that: by introducing the ergodicity, randomicity and regularity of chaos theory into PMA, the solution accuracy and the convergence property of PMA can effectively improve and effectively avoid prematurity phenomenon. The improved algorithm performs very well.
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