Global convergence enhancement of classical linesearch interior point methods for MCPs
Journal of Computational and Applied Mathematics
The Complexity of Self-Regular Proximity Based Infeasible IPMs
Computational Optimization and Applications
Interior-Point Algorithms, Penalty Methods and Equilibrium Problems
Computational Optimization and Applications
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In this work we present an infeasible-interior-point algorithm which is based on a method for the general nonlinear programming problem to solve linear complementarity problems. For this algorithm, we prove global convergence from any strictly positive starting point, under minor assumptions. Numerical results are reported which demonstrate very good computational performance on large-scale linear complementarity problems.