Abstract
We propose a scheme to solve constrained optimization problems by combining a nonlinear penalty method and a descent method. A sequence of nonlinear penalty optimization problems is solved to generate a sequence of stationary points, i.e., each point satisfies a first-order necessary optimality condition of a nonlinear penalty problem. Under some conditions, we show that any limit point of the sequence satisfies the first-order necessary condition of the original constrained optimization problem.
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Huang, X., Yang, X. Convergence Analysis of a Class of Nonlinear Penalization Methods for Constrained Optimization via First-Order Necessary Optimality Conditions. Journal of Optimization Theory and Applications 116, 311–332 (2003). https://doi.org/10.1023/A:1022503820909
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DOI: https://doi.org/10.1023/A:1022503820909