The first hitting time analysis of evolutionary algorithms based on renewal process

Author:

Zhou Zhensheng12,Wang Lin2,Zou Xue12,Wang Fei3,Zhang Zaijun45,Yan Xiaobo2

Affiliation:

1. School of Data Sciences and Information Engineering, Guizhou Minzu University, Guiyang 550025, China

2. Guizhou Key Laboratory of Pattern Recognition and Intelligent System, Guiyang 550025, China

3. College of Big Data and Information Engineering, Guiyang Institute of Humanities and Technology, Guiyang 550025, China

4. School of Mathematics and Statistics, Qiannan Normal University for Nationalities, Duyun 558000, China

5. Key Laboratory of Industrial Automation and Machine Vision of Qiannan, Duyun 558000, China

Abstract

<abstract> <p>Running time analysis of evolutionary algorithms for continuous optimization is one research challenge in the field of evolutionary algorithms (EAs). However, the theoretical analysis results have rarely been applied to evolutionary algorithms for continuous optimization in practice, let alone their variants for evolution strategy. In this paper, we regarded the first hitting time of evolution strategy as the stopping time of the renewal process on the basis of the renewal process and in combination with Wald's inequality and stopping time theory. Afterwards, to demonstrate the application of the proposed model in the first hitting time analysis of (1 + 1) ES, we analyzed it with different mutation operators on the sphere function. First, we significantly improved the lower bound on the first hitting time of (1 + 1) ES with a uniform mutation operator, i.e., from $\Omega(n)$ to $\Omega\left(e^{c n}\right)$. Next, $O\left(n^{2} \sqrt{n}\right)$ was the upper bound on the first hitting time of (1 + 1) ES with a Gaussian mutation operator from the initial distance <italic>R</italic> to half of the initial distance <italic>R</italic>/2. The numerical experimental results showed that the theoretical calculation was consistent with the actual running time, which provides a novel method for analyzing the first hitting time of EAs.</p> </abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3