城市供水网络中的鲁棒传感器配置问题

Xin Ma, Yuantao Song, Jun Huang, Jun Wu
{"title":"城市供水网络中的鲁棒传感器配置问题","authors":"Xin Ma, Yuantao Song, Jun Huang, Jun Wu","doi":"10.1109/CSO.2010.166","DOIUrl":null,"url":null,"abstract":"In this paper, we are interested in the Robust Sensor Placement Problem (RSPP) in municipal water networks. As the contamination source and time are rather random and almost impossible to forecast, we aim to minimize the maximum population exposed over all contamination scenarios by placing a limited number of sensors into the network. We formulate a mixed-integer program model based on an absolute robustness criterion and design a tabu search heuristic to solve it quickly and efficiently. At last, we use a computational experiment to illustrate the effectiveness of our approach compared to the classical methods found in most of the literature.","PeriodicalId":427481,"journal":{"name":"2010 Third International Joint Conference on Computational Science and Optimization","volume":"93 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Robust Sensor Placement Problem in Municipal Water Networks\",\"authors\":\"Xin Ma, Yuantao Song, Jun Huang, Jun Wu\",\"doi\":\"10.1109/CSO.2010.166\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we are interested in the Robust Sensor Placement Problem (RSPP) in municipal water networks. As the contamination source and time are rather random and almost impossible to forecast, we aim to minimize the maximum population exposed over all contamination scenarios by placing a limited number of sensors into the network. We formulate a mixed-integer program model based on an absolute robustness criterion and design a tabu search heuristic to solve it quickly and efficiently. At last, we use a computational experiment to illustrate the effectiveness of our approach compared to the classical methods found in most of the literature.\",\"PeriodicalId\":427481,\"journal\":{\"name\":\"2010 Third International Joint Conference on Computational Science and Optimization\",\"volume\":\"93 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-05-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Third International Joint Conference on Computational Science and Optimization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSO.2010.166\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Third International Joint Conference on Computational Science and Optimization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSO.2010.166","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10

摘要

在本文中,我们感兴趣的是鲁棒传感器安置问题(RSPP)在城市供水网络。由于污染源和时间是相当随机的,几乎不可能预测,我们的目标是通过在网络中放置有限数量的传感器来最小化所有污染场景中暴露的最大人口。基于绝对鲁棒性准则构造了一个混合整数规划模型,并设计了禁忌搜索启发式算法快速高效地求解该模型。最后,我们用一个计算实验来说明与大多数文献中发现的经典方法相比,我们的方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust Sensor Placement Problem in Municipal Water Networks
In this paper, we are interested in the Robust Sensor Placement Problem (RSPP) in municipal water networks. As the contamination source and time are rather random and almost impossible to forecast, we aim to minimize the maximum population exposed over all contamination scenarios by placing a limited number of sensors into the network. We formulate a mixed-integer program model based on an absolute robustness criterion and design a tabu search heuristic to solve it quickly and efficiently. At last, we use a computational experiment to illustrate the effectiveness of our approach compared to the classical methods found in most of the literature.
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