Using ACO Metaheuristic for MWT Problem

Maria Gisela Dorzán, Edilma Olinda Gagliardi, G. Leguizamón, Gregorio Hernández-Peñalver
{"title":"Using ACO Metaheuristic for MWT Problem","authors":"Maria Gisela Dorzán, Edilma Olinda Gagliardi, G. Leguizamón, Gregorio Hernández-Peñalver","doi":"10.1109/SCCC.2011.30","DOIUrl":null,"url":null,"abstract":"Globally optimal triangulations are difficult to be found by deterministic methods as, for most type of criteria, no polynomial algorithm is known. In this work, we consider the Minimum Weight Triangulation (MWT) problem of a given set of n points in the plane. This paper shows how the Ant Colony Optimization (ACO) metaheuristic can be used to find high quality triangulations. For the experimental study we have created a set of instances for MWT problem since no reference to benchmarks for these problems were found in the literature. Through the experimental evaluation, we assess the applicability of the ACO metaheuristic for MWT problem.","PeriodicalId":173639,"journal":{"name":"2011 30th International Conference of the Chilean Computer Science Society","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 30th International Conference of the Chilean Computer Science Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SCCC.2011.30","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

Globally optimal triangulations are difficult to be found by deterministic methods as, for most type of criteria, no polynomial algorithm is known. In this work, we consider the Minimum Weight Triangulation (MWT) problem of a given set of n points in the plane. This paper shows how the Ant Colony Optimization (ACO) metaheuristic can be used to find high quality triangulations. For the experimental study we have created a set of instances for MWT problem since no reference to benchmarks for these problems were found in the literature. Through the experimental evaluation, we assess the applicability of the ACO metaheuristic for MWT problem.
用蚁群元启发式算法求解MWT问题
全局最优三角剖分很难用确定性方法找到,因为对于大多数类型的准则,没有已知的多项式算法。在这项工作中,我们考虑了平面上给定n个点的最小权三角剖分(MWT)问题。本文展示了如何使用蚁群优化(ACO)元启发式方法来寻找高质量的三角剖分。对于实验研究,我们为MWT问题创建了一组实例,因为在文献中没有找到这些问题的基准参考。通过实验评估,我们评估了蚁群元启发式算法在MWT问题中的适用性。
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 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:604180095
Book学术官方微信