Smoothing Nonlinear Penalty Functions for Constrained Optimization Problems

In this article, we discuss a nondifferentiable nonlinear penalty method for an optimization problem with inequality constraints. A smoothing method is proposed for the nonsmooth nonlinear penalty function. Error estimations are obtained among the optimal value of smoothed penalty problem, the optimal value of the nonsmooth nonlinear penalty optimization problem and that of the original constrained optimization problem. We give an algorithm for the constrained optimization problem based on the smoothed nonlinear penalty method and prove the convergence of the algorithm. The efficiency of the smoothed nonlinear penalty method is illustrated with a numerical example.