Abstract
An algorithm is proposed for computing an unconstrained minimax, based on differential equations with suitable stabilization terms. Methods for accelerating the convergence are discussed. For computing a constrained minimax, the augmented Lagrangian algorithm of Powell, Hestenes and Rockafellar is generalized to minimax, assuming the unconstrained minimax algorithm as a subroutine. An estimate of the convergence rate is obtained.
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Craven, B.D. An algorithm for minimax. ZOR - Methods and Models of Operations Research 35, 425–434 (1991). https://doi.org/10.1007/BF01498333
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DOI: https://doi.org/10.1007/BF01498333