Modified SSOR Modelling for Linear Complementarity Problems

Modified SSOR Modelling for Linear Complementarity Problems

Where, T z denotes the transpose of the vector z . Many problems in operations research, management science, various scientific computing and engineering areas can lead to the solution of an LCP of the form (1.1). For more details (see, [1,2,3] and the references therein). The early motivation for studying the LCP (M, q) was because the KKT optimality conditions for linear and quadratic program...

Improved infeasible-interior-point algorithm for linear complementarity problems

We present a modified version of the infeasible-interior- We present a modified version of the infeasible-interior-point algorithm for monotone linear complementary problems introduced by Mansouri et al. (Nonlinear Anal. Real World Appl. 12(2011) 545--561). Each main step of the algorithm consists of a feasibility step and several centering steps. We use a different feasibility step, which tar...

A Modified Penalty Embedding for Linear Complementarity Problems

ABSTRACT We propose a modified penalty embedding for solving complementarity problem (LCP). This embedding is a special one parametric optimization problem P(t), t∈[0,1]. Under the condition (A3) (a modified Enlarged Mangasarian Fromovitz Constrait Qualification), (A4) (P(t) is JongenJonker -Twilt regular) and two technical assumptions (A1) and (A2) there exists a path in the set of stationary ...

On modified block SSOR iteration methods for linear systems from steady incompressible viscous flow problems

Matrix Linear Complementarity Problems

We consider the expected residual minimization formulation of the stochastic R0 matrix linear complementarity problem. We show that the involved matrix being a stochastic R0 matrix is a necessary and sufficient condition for the solution set of the expected residual minimization problem to be nonempty and bounded. Moreover, local and global error bounds are given for the stochastic R0 matrix li...