The covariance matrix adaptation evolution strategy (CMA-ES) is one of the most successful methods for solving continuous black-box optimization problems. A practically useful aspect of CMA-ES is that it can be used without hyperparameter tuning. However, ...

The population size adaptation mechanism for CMA-ES is evaluated on the BBOB noiseless testbed. The population size is adapted on the basis of the estimated accuracy of the update of the distribution parameters, i.e., the mean vector and the covariance ...

The multi-objective covariance matrix adaptation evolution strategy (MO-CMA-ES) is an evolutionary algorithm for continuous vector-valued optimization. It combines indicator-based selection based on the contributing hypervolume with the efficient ...