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The family of gradient-free optimization methods includes evolutionary algorithms, Bayesian optimization, simulated annealing, particle swarm optimization, and the Nelder-Mead simplex method, all sharing the common characteristic of relying solely on objective function output values without requiring continuity or differentiability.
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10/4/2026
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