{"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}
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.