@INPROCEEDINGS{KonstantinidisZY:09,
AUTHOR="Andreas Konstantinidis and Qingfu Zhang and Kun Yang",
TITLE="A Subproblem-dependent Heuristic in {MOEA/D} for the Deployment and Power Assignment Problem in Wireless Sensor Networks",
BOOKTITLE="IEEE Congress on Evolutionary Computation, CEC'09 Evolutionary Optimization",
ADDRESS="Trondheim, Norway", DAYS=, MONTH=MARCH, YEAR=2009,
KEYWORDS="deployment;power assignment;coverage;lifetime;wireless
sensor networks;multiobjective optimization;evolutionary
algorithms;decomposition;local search;adaptive heuristic;problem specific
knowledge",
ABSTRACT="In this paper, we propose a Subproblem-dependent
Heuristic (SH) for MOEA/D to deal with the Deployment and
Power Assignment Problem (DPAP) in Wireless Sensor Networks
(WSNs). The goal of the DPAP is to assign locations and transmit
power levels to sensor nodes for maximizing the network coverage
and lifetime objectives. In our method, the DPAP is decomposed
into a number of scalar subproblems. The subproblems are
optimized in parallel, by using neighborhood information and
problem-specific knowledge. The proposed SH probabilistically
alternates between two DPAP-specific strategies based on the
subproblems objective preferences. Simulation results have shown
that MOEA/D performs better than NSGA-II in several WSN
instances."}