Decomposition-Based Multiobjective Evolutionary Algorithm With an Ensemble of Neighborhood Sizes PROJECT TITLE :Decomposition-Based Multiobjective Evolutionary Algorithm With an Ensemble of Neighborhood SizesABSTRACT :The multiobjective evolutionary algorithm based on decomposition (MOEA/D) has demonstrated superior performance by winning the multiobjective optimization algorithm competition at the CEC 2009. For effective performance of MOEA/D, neighborhood size (NS) parameter needs to be tuned. In this letter, an ensemble of different NSs with online self-adaptation is proposed (ENS-MOEA/D) to overcome this shortcoming. Our experimental results on the CEC 2009 competition check instances show that an ensemble of various NSs with online self-adaptation yields superior performance over implementations with solely one mounted NS. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Using the Averaged Hausdorff Distance as a Performance Measure in Evolutionary Multiobjective Optimization A Study of Collapse in Bare Bones Particle Swarm Optimization