Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/54361
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dc.contributor.authorRungrote Kuawattanaphanen_US
dc.contributor.authorPaskorn Champraserten_US
dc.date.accessioned2018-09-04T10:12:27Z-
dc.date.available2018-09-04T10:12:27Z-
dc.date.issued2015-01-01en_US
dc.identifier.issn21945357en_US
dc.identifier.other2-s2.0-84931281729en_US
dc.identifier.other10.1007/978-3-319-19024-2_7en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84931281729&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/54361-
dc.description.abstract© Springer International Publishing Switzerland 2015. This paper proposes and evaluates a novel evolutionary selection called waterfall selection in a multi-objective optimization evolutionary algorithm for a priority-based wireless sensor nodes redeployment problem. Since, there are a variety of sensor node types in a target area. Each sensor node may have different objectives (E.g., network lifetime, data transmission, and success rate). Practically, the objectives of sensor nodes are prioritized after the deployment process. This paper focuses on the redeployment process of wireless sensor nodes to achieve their prioritized objectives simultaneously. Simulation results show that the proposed novel waterfall selection in multi-objective optimization evolutionary algorithm seeks to the solutions that conform to the prioritized objectives in timely manner and outperforms a NSGA-II evolutionary algorithm for multi-objective optimization.en_US
dc.subjectComputer Scienceen_US
dc.subjectEngineeringen_US
dc.titlePrioritized multiobjective optimization in WSN redeployment using waterfall selectionen_US
dc.typeBook Seriesen_US
article.title.sourcetitleAdvances in Intelligent Systems and Computingen_US
article.volume361en_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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