Decomposition-based multiobjective evolutionary algorithm with an ensemble of neighborhood sizes.
Suganthan, P. N.
Zhang, Qing Fu.
Date of Issue2012
School of Electrical and Electronic Engineering
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.
DRNTU::Engineering::Electrical and electronic engineering
IEEE transactions on evolutionary computation