“…Therefore, to improve the locally convergent nature of most algorithms, recent research has been devoted to creating globally convergent methods. These solution methods for the variational inequality problems can be classified into three categories: (1) transforming into nonsmooth equations (or, fixed-point problems) and then being solved by semismooth Newton-type methods, smoothing Newton methods, continuation method or projective methods (see, e.g., [4][5][6][7]2,[8][9][10]); (2) reformulating as optimization problems and then being solved by some algorithms for optimization problems (see, e.g., [11][12][13]); (3) solving KKT systems of the variational inequality problems similarly with KKT system of constrained optimization (homotopy methods, e.g., [14][15][16]). However, the convergence of many algorithms were established when the mapping F is assumed to have some monotonicity.…”