Active-set approaches are commonly used in algorithms for constrained numerical optimization. We propose that active-set techniques can beneficially be employed for evolutionary black-box optimization with explicit constraints and present an activeset evolution strategy. We experimentally evaluate its performance relative to those of several algorithms for constrained optimization and find that the active-set evolution strategy compares favourably for the problem set under consideration.

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