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In this paper, the authors propose a Sub-problem-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 their method, the DPAP is decomposed into a number of scalar sub-problems. The sub-problems 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 sub-problems objective preferences. Simulation results have shown that MOEA/D performs better than NSGA-II in several WSN instances.
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