An implementation of a discretization method for semi-infinite programming
Mathematical Programming: Series A and B
A note on an implementation of a method for quadratic semi-infinite programming
Mathematical Programming: Series A and B
Discretization methods for the solution of semi-infinite programming problems
Journal of Optimization Theory and Applications
A nonsmooth version of Newton's method
Mathematical Programming: Series A and B
Numerical experiments in semi-infinite programming
Computational Optimization and Applications
Computational Optimization and Applications - Special issue on computational optimization—a tribute to Olvi Mangasarian, part II
Semismooth Newton Methods for Solving Semi-Infinite Programming Problems
Journal of Global Optimization
A Smoothing Newton Method for Semi-Infinite Programming
Journal of Global Optimization
Grey-prediction self-organizing fuzzy controller for robotic motion control
Information Sciences: an International Journal
Smoothing SQP algorithm for semismooth equations with box constraints
Computational Optimization and Applications
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In this paper, we first transform the semi-infinite programming problem into the KKT system by the techniques in [D.H. Li, L. Qi, J. Tam, S.Y. Wu, A smoothing Newton method for semi-infinite programming, J. Global. Optim. 30 (2004) 169-194; L. Qi, S.Y. Wu, G.L. Zhou, Semismooth Newton methods for solving semi-infinite programming problems, J. Global. Optim. 27 (2003) 215-232]. Then a nonsmooth and inexact Levenberg-Marquardt method is proposed for solving this KKT system based on [H. Dan, N. Yamashita, M. Fukushima, Convergence properties of the inexact Levenberg-Marquardt method under local error bound conditions, Optimim. Methods Softw., 11 (2002) 605-626]. This method is globally and superlinearly (even quadratically) convergent. Finally, some numerical results are given.