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Decomposition-Based Multiobjective Evolutionary Algorithm With an Ensemble of Neighborhood Sizes

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3 Author(s)
Shi-Zheng Zhao ; School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore ; Ponnuthurai Nagaratnam Suganthan ; Qingfu Zhang

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 has 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 test instances show that an ensemble of different NSs with online self-adaptation yields superior performance over implementations with only one fixed NS.

Published in:

IEEE Transactions on Evolutionary Computation  (Volume:16 ,  Issue: 3 )