An ant colony optimization heuristic for solving maximum independent set problems

Youmei Li, Z. Xul
{"title":"An ant colony optimization heuristic for solving maximum independent set problems","authors":"Youmei Li, Z. Xul","doi":"10.1109/ICCIMA.2003.1238126","DOIUrl":null,"url":null,"abstract":"In this paper, ant colony optimization heuristic is extended for solving maximum independent set (MIS) problems. MIS problems are quite different from the travelling salesman problems (TSP) etc., in which no concept of \"path or order\" exists in its solutions. Based on such characteristics, the ant colony optimization heuristic is modified in this paper in the following ways: (i) a new computation method for heuristic information is adapted; (ii) the pheromone update rule is augmented; (iii) a complement solution construction process is designed. The simulation shows that the proposed ant colony optimization heuristic is effective and efficient for MIS problems.","PeriodicalId":385362,"journal":{"name":"Proceedings Fifth International Conference on Computational Intelligence and Multimedia Applications. ICCIMA 2003","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"44","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Fifth International Conference on Computational Intelligence and Multimedia Applications. ICCIMA 2003","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIMA.2003.1238126","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 44

Abstract

In this paper, ant colony optimization heuristic is extended for solving maximum independent set (MIS) problems. MIS problems are quite different from the travelling salesman problems (TSP) etc., in which no concept of "path or order" exists in its solutions. Based on such characteristics, the ant colony optimization heuristic is modified in this paper in the following ways: (i) a new computation method for heuristic information is adapted; (ii) the pheromone update rule is augmented; (iii) a complement solution construction process is designed. The simulation shows that the proposed ant colony optimization heuristic is effective and efficient for MIS problems.
求解最大独立集问题的蚁群优化启发式算法
本文将蚁群优化启发式算法推广到求解最大独立集问题。MIS问题与旅行推销员问题(TSP)等问题有很大的不同,在这些问题的解中不存在“路径或顺序”的概念。基于这一特点,本文对蚁群优化启发式算法进行了如下改进:(1)采用了一种新的启发式信息计算方法;(ii)信息素更新规则增强;(三)设计了补解构建流程。仿真结果表明,提出的蚁群优化启发式算法对管理信息系统问题是有效的。
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