@INPROCEEDINGS{KonstantinidisYZ:08,
AUTHOR="Andreas Konstantinidis and Kun Yang and Qingfu Zhang",
TITLE="An Evolutionary Algorithm to a Multi-Objective Deployment and
Power Assignment Problem in Wireless Sensor Networks",
BOOKTITLE=" Global Telecommunications Conference, 2008. IEEE GLOBECOM 2008. IEEE",
ADDRESS=" New Orleans, LO", DAYS=30, MONTH=11, YEAR=2008,
KEYWORDS="deployment;power assignment;coverage;lifetime;wireless
sensor networks;multiobjective optimization;evolutionary
algorithms;decomposition;encoding;genetic operation;problem specific
knowledge",
ABSTRACT="Wireless sensor networks design requires high quality location assignment and energy efficient power assignment for maximizing the network coverage and lifetime. Classical deployment and power assignment 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 article a multi-objective deployment and power assignment problem (DPAP) is formulated and a multi-objective evolutionary algorithm based on decomposition (MOEA/D) is specialized. Following the MOEA/D's framework the above multiobjective optimization problem (MOP) is decomposed into many scalar single objective problems. The sub-problems are solved simultaneously by using neighborhood information. Additionally, unique problem-specific, parameter-rising, genetic operators and local search heuristics were designed specifically for the DPAP. In addition, a new encoding scheme is designed to represent a WSN based on the DPAP's design variables. Simulation results show that MOEA/D provides a high quality set of alternative solutions without any prior knowledge on the objectives preference."}