Theoretical Mathematics & Applications

Second-order smoothing approximation to l1 exact penalty function for nonlinear constrained optimization problems

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  • Abstract

    In this paper, a second-order smoothing approximation to the l1 exact penalty function for nonlinear constrained optimization problems is presented. Error estimations are obtained among the optimal objective function values of the smoothed penalty problem, of the nonsmooth penalty problem and of the original optimization problem. Based on the smoothed penalty problem, an algorithm that has better convergence is presented. Numerical examples illustrate that this algorithm is efficient in solving nonlinear constrained optimization problems.