Theory of linear and integer programming
Theory of linear and integer programming
On the finite convergence of interior-point algorithms for linear programming
Mathematical Programming: Series A and B
On the convergence of the exponential multiplier method for convex programming
Mathematical Programming: Series A and B
The Generalized Order Linear Complementarity Problem
SIAM Journal on Matrix Analysis and Applications
Finding an interior point in the optimal face of linear programs
Mathematical Programming: Series A and B
Nonlinear mappings associated with the generalized linear complementarity problem
Mathematical Programming: Series A and B
On the entropic perturbation and exponential penalty methods for linear programming
Journal of Optimization Theory and Applications
The generalized linear complementarity problem revisited
Mathematical Programming: Series A and B
On finite termination of an iterative method for linear complementarity problems
Mathematical Programming: Series A and B
Mathematics of Operations Research
On Homotopy-Smoothing Methods for Box-Constrained Variational Inequalities
SIAM Journal on Control and Optimization
A Smoothing Newton Method for Extended Vertical Linear Complementarity Problems
SIAM Journal on Matrix Analysis and Applications
Improving the convergence of non-interior point algorithms for nonlinear complementarity problems
Mathematics of Computation
Computational Optimization and Applications - Special issue on nonsmooth and smoothing methods
Sub-quadratic convergence of a smoothing Newton algorithm for the P0– and monotone LCP
Mathematical Programming: Series A and B
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By using a smooth entropy function to approximate the non-smooth max-type function, a vertical linear complementarity problem (VLCP) can be treated as a family of parameterized smooth equations. A Newton-type method with a testing procedure is proposed to solve such a system. We show that under some milder than usual assumptions the proposed algorithm finds an exact solution of VLCP in a finite number of iterations. Some computational results are included to illustrate the potential of this approach.