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Problem-specific encoding and genetic operation for a multi-objective deployment and power assignment problem in wireless sensor networks

Andreas Konstantinidis, Kun Yang, Qingfu Zhang

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

Wireless Sensor Networks Deployment and Power Assignment Problems (DPAPs) for maximizing the network coverage and lifetime respectively, have received increasing attention recently. Classical approaches optimize these two objectives individually, or by combining them together in a single objective, or by constraining one and optimizing the other. In this paper, the two problems are formulated as a multi-objective DPAP and tackled simultaneously. Problem-specific encoding representation and genetic operators are designed for the DPAP and a Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) is specialized. The multi-objective DPAP is decomposed into many scalar subproblems which are solved simultaneously by using neighborhood information and network knowledge. Simulation results have shown the effectiveness of the proposed evolutionary components by providing a high quality set of alternative solutions without any prior knowledge on the objectives preference, and the superiority of our problem-specific MOEA/D approach against a state of the art MOEA. ©2009 Crown.
Original languageEnglish
Title of host publicationIEEE International Conference on Communications
DOIs
Publication statusPublished - 2009
Externally publishedYes
Event2009 IEEE International Conference on Communications, ICC 2009 - Dresden, Germany
Duration: 14 Jun 200918 Jun 2009

Publication series

Name
ISSN (Print)0536-1486

Conference

Conference2009 IEEE International Conference on Communications, ICC 2009
PlaceGermany
CityDresden
Period14/06/0918/06/09

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