Superlinear Convergence of an Infeasible Predictor-Corrector Path-Following Interior Point Algorithm for a Semidefinite Linear Complementarity Problem Using the Helmberg–Kojima–Monteiro Direction

2011 ◽  
Vol 21 (1) ◽  
pp. 102-126 ◽  
Author(s):  
Chee-Khian Sim
Keyword(s):  
Linear Complementarity Problem ◽  
Interior Point ◽  
Superlinear Convergence ◽  
Complementarity Problem ◽  
Path Following ◽  
Linear Complementarity ◽  
Interior Point Algorithm ◽  
Predictor Corrector ◽  
Semidefinite Linear Complementarity Problem

scholarly journals Numerical Results for the General Linear Complementarity Problem

2019 ◽  
Vol 11 (1) ◽  
pp. 43-46
Author(s):  
Zsolt Darvay ◽  
Ágnes Füstös
Keyword(s):  
Programming Language ◽  
Linear Complementarity Problem ◽  
Interior Point ◽  
Complementarity Problem ◽  
Complementarity Problems ◽  
Linear Complementarity ◽  
Numerical Results ◽  
Interior Point Algorithm ◽  
C Programming Language ◽  
C Programming

Abstract In this article we discuss the interior-point algorithm for the general complementarity problems (LCP) introduced by Tibor Illés, Marianna Nagy and Tamás Terlaky. Moreover, we present a various set of numerical results with the help of a code implemented in the C++ programming language. These results support the efficiency of the algorithm for both monotone and sufficient LCPs.

A primal-dual interior-point method based on a new kernel function for linear complementarity problem

2019 ◽  
Vol 12 (07) ◽  
pp. 2050001
Author(s):  
El Amir Djeffal ◽  
Mounia Laouar
Keyword(s):  
Linear Complementarity Problem ◽  
Interior Point ◽  
Complementarity Problem ◽  
Small Neighborhood ◽  
Linear Complementarity ◽  
Central Path ◽  
Search Direction ◽  
Interior Point Algorithm ◽  
Newton Step ◽  
Primal Dual

In this paper, we present an interior-point algorithm for solving an optimization problem using the central path method. By an equivalent reformulation of the central path, we obtain a new search direction which targets at a small neighborhood of the central path. For a full-Newton step interior-point algorithm based on this search direction, the complexity bound of the algorithm is the best known for linear complementarity problem. For its numerical tests, some strategies are used and indicate that the algorithm is efficient.

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