Abstract
A well-known approach to constrained minimization is via a sequence of unconstrained optimization computations applied to a penalty function. This paper shows how it is possible to generalize Murphy's penalty method for differentiable problems of mathematical programming (Ref. 1) to solve nondifferentiable problems of finding saddle points with constraints. As in mathematical programming, it is shown that the method has the advantages of both Fiacco and McCormick exterior and interior penalty methods (Ref. 2). Under mild assumptions, the method has the desirable property that all trial solutions become feasible after a finite number of iterations. The rate of convergence is also presented. It should be noted that the results presented here have been obtained without making any use of differentiability assumptions.
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Communicated by A. V. Fiacco
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Strodiot, J.J., Nguyen, V.H. An exponential penalty method for nondifferentiable minimax problems with general constraints. J Optim Theory Appl 27, 205–219 (1979). https://doi.org/10.1007/BF00933227
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DOI: https://doi.org/10.1007/BF00933227