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A Confidence-Driven Evolutionary Algorithm for Noisy Optimization with Joint Chance Constraints
Many real-world optimization problems involve noisy objective evaluations and probabilistic constraints, particularly in the form of joint chance constraints, which are computationally expensive to evaluate. In this work, we propose CR-EA-C, a confidence-driven evolutionary algorithm for solving noi
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