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This paper modifies the replacement and update scheme in MOEA/D-DE developed in for dealing with constraints in multiobjective optimization problems. The modified scheme introduces a penalty function to penalize infeasible solutions. The penalty function uses a threshold to control the amount of penalty to infeasible solutions. Experimental results have shown that this penalty method is very promising.
The K-connected deployment and power assignment problem (DPAP) in WSNs aims at deciding both the sensor locations and transmit power levels, for maximizing both the network coverage and lifetime under K-connectivity constraints, in a single run. It is shown that the multi-objective evolutionary algorithm based on decomposition (MOEA/D) is a strong enough tool for dealing with unconstraint real life...
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