@INPROCEEDINGS{KonstantinidisYZ:09,
AUTHOR="Andreas Konstantinidis and Kun Yang and Qingfu Zhang",
TITLE="Problem-specific Encoding and Genetic Operation for a
{Multi-Objective} Deployment and Power Assignment Problem in
Wireless Sensor Networks",
BOOKTITLE="ICC 2009 Ad Hoc and Sensor Networking Symposium",
ADDRESS="Dresden, Germany, Germany", DAYS=14, MONTH=6, YEAR=2009,
KEYWORDS="deployment;power assignment;coverage;lifetime;wireless
sensor networks;multiobjective optimization;evolutionary
algorithms;decomposition;encoding;genetic operation;problem specific
knowledge",
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 into a multiobjective 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."}