{"title":"Multi-objective optimization algorithms for sensor network design","authors":"R. Rajagopalan","doi":"10.1109/WAMICON.2010.5461875","DOIUrl":null,"url":null,"abstract":"Many sensor network design problems are characterized by the need to optimize multiple objectives. However, existing techniques in sensor network design generally optimize only one objective while treating the others as constraints or convert the multi-objective optimization problem into a single objective optimization problem using weights associated with different objectives. The weighted sum approach is subjective and is incapable of obtaining multiple tradeoff solutions for non-convex optimization problems. A multi-objective optimization approach optimizes all objectives simultaneously and obtains multiple tradeoff solutions for non-convex problems without the need for a weight vector. This paper illustrates this approach by formulating and solving the sensor placement problem for energy efficient target detection as a multi-objective optimization problem.","PeriodicalId":112402,"journal":{"name":"2010 IEEE 11th Annual Wireless and Microwave Technology Conference (WAMICON)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE 11th Annual Wireless and Microwave Technology Conference (WAMICON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WAMICON.2010.5461875","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
Many sensor network design problems are characterized by the need to optimize multiple objectives. However, existing techniques in sensor network design generally optimize only one objective while treating the others as constraints or convert the multi-objective optimization problem into a single objective optimization problem using weights associated with different objectives. The weighted sum approach is subjective and is incapable of obtaining multiple tradeoff solutions for non-convex optimization problems. A multi-objective optimization approach optimizes all objectives simultaneously and obtains multiple tradeoff solutions for non-convex problems without the need for a weight vector. This paper illustrates this approach by formulating and solving the sensor placement problem for energy efficient target detection as a multi-objective optimization problem.