Applying k-means Method to the Modified Bottleneck Assignment Problem in Vector Case

Y. Kamura
{"title":"Applying k-means Method to the Modified Bottleneck Assignment Problem in Vector Case","authors":"Y. Kamura","doi":"10.1109/CCWC47524.2020.9031191","DOIUrl":null,"url":null,"abstract":"In this study, we deal with the vector case's bottleneck assignment problem. Each edge's cost is introduced by the sum of the vertices which are assigned. This problem is NP-complete. We show an idea that we use a clustering method to divide the problem to partial ones. Each vertices' set is divided into subsets by a non-hierarchical clustering method. We make the optimal combination of the subsets, then vertices in the subset are corresponded according to the subsets' combinations. We examine our proposed algorithm in effectiveness by numerical experiments.","PeriodicalId":161209,"journal":{"name":"2020 10th Annual Computing and Communication Workshop and Conference (CCWC)","volume":"55 4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 10th Annual Computing and Communication Workshop and Conference (CCWC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCWC47524.2020.9031191","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

In this study, we deal with the vector case's bottleneck assignment problem. Each edge's cost is introduced by the sum of the vertices which are assigned. This problem is NP-complete. We show an idea that we use a clustering method to divide the problem to partial ones. Each vertices' set is divided into subsets by a non-hierarchical clustering method. We make the optimal combination of the subsets, then vertices in the subset are corresponded according to the subsets' combinations. We examine our proposed algorithm in effectiveness by numerical experiments.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
k-均值法在矢量情况下改进瓶颈分配问题中的应用
在本研究中,我们处理向量情况下的瓶颈分配问题。每条边的代价是由分配的顶点的和引入的。这个问题是np完全的。提出了一种利用聚类方法将问题划分为部分问题的思路。每个顶点集通过非分层聚类方法划分为子集。我们对子集进行最优组合,然后根据子集的组合对子集中的顶点进行对应。通过数值实验验证了算法的有效性。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Environmental Perception in Autonomous Vehicles Using Edge Level Situational Awareness Secure5G: A Deep Learning Framework Towards a Secure Network Slicing in 5G and Beyond Focus Detection Using Spatial Release From Masking An Intrusion Detection System Against DDoS Attacks in IoT Networks The self- upgrading mobile application for the automatic malaria detection
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1