Nonsmooth Levenberg-Marquardt type method for solving a class of stochastic linear complementarity problems with finitely many elements (Q1736870)

Summary: Our purpose of this paper is to solve a class of stochastic linear complementarity problems (SLCP) with finitely many elements. Based on a new stochastic linear complementarity problem function, a new semi-smooth least squares reformulation of the stochastic linear complementarity problem is introduced. For solving the semi-smooth least squares reformulation, we propose a feasible nonsmooth Levenberg-Marquardt-type method. The global convergence properties of the nonsmooth Levenberg-Marquardt-type method are also presented. Finally, the related numerical results illustrate that the proposed method is efficient for the related refinery production problem and the large-scale stochastic linear complementarity problems.