On the Smoothing of the Square-Root Exact Penalty Function for Inequality Constrained Optimization

Authors:
Zhiqing Meng;Chuangyin Dang;Xiaoqi Yang
Affiliations:
College of Business and Administration, Zhejiang University of Technology, Hangzhou, China 310032;Department of Manufacturing Engineering & Engineering Management, City University of Hong Kong, Kowloon, Hong Kong;Department of Applied Mathematics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong
Venue:
Computational Optimization and Applications
Year:
2006

Citing 4
Cited 2

An exact penalty function method with global convergence properties for nonlinear programming problems

Mathematical Programming: Series A and B
On the exactness of a class of nondifferentiable penalty functions

Journal of Optimization Theory and Applications
Smoothing methods for convex inequalities and linear complementarity problems

Mathematical Programming: Series A and B
Semismooth Newton Methods for Solving Semi-Infinite Programming Problems

Journal of Global Optimization

A penalty function method based on smoothing lower order penalty function

Journal of Computational and Applied Mathematics
A new class of exact penalty functions and penalty algorithms

Journal of Global Optimization

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper we propose two methods for smoothing a nonsmooth square-root exact penalty function for inequality constrained optimization. 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. We develop an algorithm for solving the optimization problem based on the smoothed penalty function and prove the convergence of the algorithm. The efficiency of the smoothed penalty function is illustrated with some numerical examples, which show that the algorithm seems efficient.