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Covariance matrix adaptation evolution strategies (CMA-ES) is a powerful optimizer. In this paper, we propose an efficient rank-1 update for the Cholesky covariance matrix adaptation evolution strategy (Cholesky CMA-ES) using an auxiliary evolution path. It accumulates the average mutation vector corresponding to the current search direction, which is used to update the evolution path. It is used...
The bias feature is a major factor that makes a multiobjective optimization problem (MOP) difficult for multiobjective evolutionary algorithms (MOEAs). To deal with this problem feature, an algorithm should carefully balance between exploration and exploitation. The decomposition-based MOEA decomposes an MOP into a number of single objective subproblems and solves them in a collaborative manner. Single...
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