Computational Optimization and Applications - Special issue on computational optimization—a tribute to Olvi Mangasarian, part II
Global Optimization Techniques for Mixed Complementarity Problems
Journal of Global Optimization
NCP Functions Applied to Lagrangian Globalization for the Nonlinear Complementarity Problem
Journal of Global Optimization
Merit Functions for Complementarity and Related Problems: A Survey
Computational Optimization and Applications
Smoothing Newton and Quasi-Newton Methods for Mixed Complementarity Problems
Computational Optimization and Applications
Computational Optimization and Applications
A smoothing Broyden-like method for the mixed complementarity problems
Mathematical and Computer Modelling: An International Journal
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In this paper we propose a new unconstrained differentiable merit function f for box constrained variational inequality problems VIP(l,u,F). We study various desirable properties of this new merit function f and propose a Gauss--Newton method in which each step requires only the solution of a system of linear equations. Global and superlinear convergence results for VIP(l,u,F) are obtained. Key results are the boundedness of the level sets of the merit function for any uniform P-function and the superlinear convergence of the algorithm without a nondegeneracy assumption. Numerical experiments confirm the good theoretical properties of the method.