@inproceedings{77843e085ea64b2db76fd36dd9d9b739,
title = "Dynamic and evolutionary multi-objective optimization for sensor selection in sensor networks for target tracking",
abstract = "When large sensor networks are applied to the task of target tracking, it is necessary to successively identify subsets of sensors that are most useful at each time instant. Such a task involves simultaneously maximizing target detection accuracy and minimizing querying cost, addressed in this paper by the application of multi-objective evolutionary algorithms (MOEAs). NSGA-II, a well-known MOEA, is demonstrated to be successful in obtaining diverse solutions (trade-off points), when compared to a {"}weighted sum{"} approach that combines both objectives into a single cost function. We also explore an improvement, LS-DNSGA, which incorporates periodic local search into the algorithm, and outperforms standard NSGA-II on the sensor selection problem.",
keywords = "Genetic algorithms, Multi-objective optimization, PCRLB, Sensor networks, Target tracking",
author = "Nikhil Padhye and Long Zuo and Mohan, {Chilukuri K.} and Varshney, {Pramod K.}",
year = "2009",
language = "English (US)",
isbn = "9789896740146",
series = "IJCCI 2009 - International Joint Conference on Computational Intelligence, Proceedings",
pages = "160--167",
booktitle = "IJCCI 2009 - International Joint Conference on Computational Intelligence, Proceedings",
note = "1st International Joint Conference on Computational Intelligence, IJCCI 2009 ; Conference date: 05-10-2009 Through 07-10-2009",
}