Chaos elitism estimation of distribution algorithm

Qingyang Xu
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引用次数: 2

Abstract

Estimation of distribution algorithm (EDA) is a kind of EAs, which is based on the technique of probabilistic model and sampling. This paper presents a chaos elitism EDA to improve the performance of traditional EDA to solve high dimensional optimization problems. The famous elitism strategy is introduced to maintain a good convergent performance. The chaos perturbation strategy is used to improve the local search ability. Some simulation experiments conducted to verify the performance of CEEDA. The results of CEEDA are promising, and it is comparable with other EDA.
混沌精英估计分布算法
分布估计算法(EDA)是一种基于概率模型和抽样技术的概率估计算法。为了解决高维优化问题,提出了一种混沌精英EDA,改进了传统EDA的性能。为了保持良好的收敛性能,引入了著名的精英策略。采用混沌摄动策略提高了局部搜索能力。通过仿真实验验证了CEEDA的性能。CEEDA的结果是有希望的,与其他EDA具有可比性。
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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