交互多目标进化算法中参考向量与不同类型偏好信息的连接

Jussi Hakanen, Tinkle Chugh, Karthik Sindhya, Yaochu Jin, K. Miettinen
{"title":"交互多目标进化算法中参考向量与不同类型偏好信息的连接","authors":"Jussi Hakanen, Tinkle Chugh, Karthik Sindhya, Yaochu Jin, K. Miettinen","doi":"10.1109/SSCI.2016.7850220","DOIUrl":null,"url":null,"abstract":"We study how different types of preference information coming from a human decision maker can be utilized in an interactive multiobjective evolutionary optimization algorithm (MOEA). The idea is to convert different types of preference information into a unified format which can then be utilized in an interactive MOEA to guide the search towards the most preferred solution(s). The format chosen here is a set of reference vectors which is used within the interactive version of the reference vector guided evolutionary algorithm (RVEA). The proposed interactive RVEA is then applied to the multiple-disk clutch brake design problem with five objectives to demonstrate the potential of the idea in supporting decision making in optimization problems involving more than three objectives.","PeriodicalId":120288,"journal":{"name":"2016 IEEE Symposium Series on Computational Intelligence (SSCI)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"25","resultStr":"{\"title\":\"Connections of reference vectors and different types of preference information in interactive multiobjective evolutionary algorithms\",\"authors\":\"Jussi Hakanen, Tinkle Chugh, Karthik Sindhya, Yaochu Jin, K. Miettinen\",\"doi\":\"10.1109/SSCI.2016.7850220\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We study how different types of preference information coming from a human decision maker can be utilized in an interactive multiobjective evolutionary optimization algorithm (MOEA). The idea is to convert different types of preference information into a unified format which can then be utilized in an interactive MOEA to guide the search towards the most preferred solution(s). The format chosen here is a set of reference vectors which is used within the interactive version of the reference vector guided evolutionary algorithm (RVEA). The proposed interactive RVEA is then applied to the multiple-disk clutch brake design problem with five objectives to demonstrate the potential of the idea in supporting decision making in optimization problems involving more than three objectives.\",\"PeriodicalId\":120288,\"journal\":{\"name\":\"2016 IEEE Symposium Series on Computational Intelligence (SSCI)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"25\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE Symposium Series on Computational Intelligence (SSCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SSCI.2016.7850220\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Symposium Series on Computational Intelligence (SSCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSCI.2016.7850220","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 25

摘要

我们研究了如何在交互式多目标进化优化算法(MOEA)中利用来自人类决策者的不同类型的偏好信息。其想法是将不同类型的偏好信息转换为统一的格式,然后可以在交互式MOEA中使用,以指导搜索最喜欢的解决方案。这里选择的格式是在参考向量引导进化算法(RVEA)的交互版本中使用的一组参考向量。然后将所提出的交互式RVEA应用于具有五个目标的多盘离合器制动器设计问题,以证明该思想在支持涉及三个以上目标的优化问题中的决策方面的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Connections of reference vectors and different types of preference information in interactive multiobjective evolutionary algorithms
We study how different types of preference information coming from a human decision maker can be utilized in an interactive multiobjective evolutionary optimization algorithm (MOEA). The idea is to convert different types of preference information into a unified format which can then be utilized in an interactive MOEA to guide the search towards the most preferred solution(s). The format chosen here is a set of reference vectors which is used within the interactive version of the reference vector guided evolutionary algorithm (RVEA). The proposed interactive RVEA is then applied to the multiple-disk clutch brake design problem with five objectives to demonstrate the potential of the idea in supporting decision making in optimization problems involving more than three objectives.
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
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信