André Barthelmes

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Many practical optimization problems are constrained black boxes. Covariance Matrix Adaptation Evolution Strategies (CMA-ES) belong to the most successful black box optimization methods. Up to now no sophisticated constraint handling method for Covariance Matrix Adaptation optimizers has been proposed. In our novel approach we learn a meta-model of the(More)
Evolution strategies are successful black-box optimization methods. But many practical numerical problems are constrained. Whenever the optimum lies in the vicinity of the constraint boundary, the success rates decrease and make successful random mutations almost impossible. Low success rates result in premature step size reduction and finally lead to(More)
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