Using vector divisions in solving linear complementarity problem
Youssef Elfoutayeni (LMDP), Mohamed Khaladi (LMDP)

TL;DR
This paper introduces a globally convergent hybrid algorithm for solving the linear complementarity problem by transforming it into a nonlinear equation and approximating it with smooth functions, supported by numerical examples.
Contribution
The paper develops a new hybrid method based on vector divisions and secant method, using smooth function sequences to solve the linear complementarity problem.
Findings
The proposed algorithm converges globally.
The method effectively solves the nonlinear equation equivalent to the LCP.
Numerical examples demonstrate the algorithm's practical performance.
Abstract
The linear complementarity problem is to find vector in satisfying , , where as a matrix and as a vector, are given data; this problem becomes in present the subject of much important research because it arises in many areas and it includes important fields, we cite for example the linear and nonlinear programming, the convex quadratic programming and the variational inequalities problems, ... It is known that the linear complementarity problem is completely equivalent to solving nonlinear equation with is a function from into itself defined by . In this paper we propose a globally convergent hybrid algorithm for solving this equation; this method is based on an algorithm given by Shi \cite{Y. Shi}, he uses vector divisions with the secant method; but for…
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