Network expansion planning using linkage identification genetic algorithm

M. Okabe, H. Aoki
{"title":"Network expansion planning using linkage identification genetic algorithm","authors":"M. Okabe, H. Aoki","doi":"10.1109/PECON.2012.6450210","DOIUrl":null,"url":null,"abstract":"This paper presents the application of multi-objective optimization method for Network Expansion Planning. The Distribution Network Expansion Planning (DNEP) aims to minimize the cost and distribution loss while satisfying the constraints. The problem formulation results in combinatorial optimization problems which in practice are quite hard to solve due to their complexity. Therefore, in this paper Genetic Algorithm which is a meta-heuristics method was applied. The present study proposed the new method of multi-objective optimization methods. NSGA-II and SPEA2 is assumed to be the best method now. The proposed method introduces the concept of linkage identification genetic algorithm into that method. As a result, new method was possible to search more efficiently than existing methods.","PeriodicalId":135966,"journal":{"name":"2012 IEEE International Conference on Power and Energy (PECon)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE International Conference on Power and Energy (PECon)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PECON.2012.6450210","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

This paper presents the application of multi-objective optimization method for Network Expansion Planning. The Distribution Network Expansion Planning (DNEP) aims to minimize the cost and distribution loss while satisfying the constraints. The problem formulation results in combinatorial optimization problems which in practice are quite hard to solve due to their complexity. Therefore, in this paper Genetic Algorithm which is a meta-heuristics method was applied. The present study proposed the new method of multi-objective optimization methods. NSGA-II and SPEA2 is assumed to be the best method now. The proposed method introduces the concept of linkage identification genetic algorithm into that method. As a result, new method was possible to search more efficiently than existing methods.
基于连锁识别遗传算法的网络扩展规划
本文介绍了多目标优化方法在网络扩展规划中的应用。配电网扩展规划(DNEP)的目标是在满足约束条件的前提下,使配电网的成本和配电损失最小化。问题的表述导致了组合优化问题,由于其复杂性,在实践中很难求解。因此,本文采用了一种元启发式方法——遗传算法。本研究提出了一种新的多目标优化方法。NSGA-II和SPEA2被认为是目前最好的方法。在该方法中引入了连锁识别遗传算法的概念。因此,新方法可以比现有方法更有效地进行搜索。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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