动态优化问题中的接管时间

2013 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments (CIDUE) Pub Date : 2013-04-16 DOI:10.1109/CIDUE.2013.6595768

Yesnier Bravo, Gabriel Luque, E. Alba

{"title":"动态优化问题中的接管时间","authors":"Yesnier Bravo, Gabriel Luque, E. Alba","doi":"10.1109/CIDUE.2013.6595768","DOIUrl":null,"url":null,"abstract":"The analysis of selection pressure is a mathematical tool that has been traditionally used for studying the dynamics of population-based optimization algorithms in stationary environments, but in dynamic optimization problems (DOPs) it is still an open issue. Common metrics such as growth curve and takeover time have no clear meaning when the problem changes over time. In this article, we propose a new definition of takeover time for DOPs. For the sake of clarity, we focus on evolutionary algorithms (EA), but results could be extended to other population-based algorithms. A model for calculating takeover time values is proposed and then its accuracy is later experimentally validated.","PeriodicalId":133590,"journal":{"name":"2013 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments (CIDUE)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Takeover time in dynamic optimization problems\",\"authors\":\"Yesnier Bravo, Gabriel Luque, E. Alba\",\"doi\":\"10.1109/CIDUE.2013.6595768\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The analysis of selection pressure is a mathematical tool that has been traditionally used for studying the dynamics of population-based optimization algorithms in stationary environments, but in dynamic optimization problems (DOPs) it is still an open issue. Common metrics such as growth curve and takeover time have no clear meaning when the problem changes over time. In this article, we propose a new definition of takeover time for DOPs. For the sake of clarity, we focus on evolutionary algorithms (EA), but results could be extended to other population-based algorithms. A model for calculating takeover time values is proposed and then its accuracy is later experimentally validated.\",\"PeriodicalId\":133590,\"journal\":{\"name\":\"2013 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments (CIDUE)\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-04-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments (CIDUE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIDUE.2013.6595768\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments (CIDUE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIDUE.2013.6595768","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 2

摘要

选择压力分析是一种传统的数学工具，用于研究静态环境下基于种群的优化算法的动力学问题，但在动态优化问题(DOPs)中，它仍然是一个开放的问题。当问题随时间变化时，增长曲线和接管时间等常见指标就没有明确的意义了。在本文中，我们提出了一个新的接管时间的定义。为了清晰起见，我们将重点放在进化算法(EA)上，但结果可以扩展到其他基于种群的算法。提出了一种计算接管时间值的模型，并通过实验验证了模型的准确性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Takeover time in dynamic optimization problems

The analysis of selection pressure is a mathematical tool that has been traditionally used for studying the dynamics of population-based optimization algorithms in stationary environments, but in dynamic optimization problems (DOPs) it is still an open issue. Common metrics such as growth curve and takeover time have no clear meaning when the problem changes over time. In this article, we propose a new definition of takeover time for DOPs. For the sake of clarity, we focus on evolutionary algorithms (EA), but results could be extended to other population-based algorithms. A model for calculating takeover time values is proposed and then its accuracy is later experimentally validated.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2013 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments (CIDUE)

自引率

0.00%

发文量