Iterative algorithms for solving generalized nonlinear mixed variational inequalities

A new concept of g-partially relaxed strong monotonicity of mappings is introduced. By applying the auxiliary variational inequality technique, some new predictor-corrector iterative algorithms for solving generalized nonlinear mixed variational inequalities are suggested and analyzed. The convergence of the algorithms only need the continuity and the g-partially relaxed strongly monotonicity of mappings. These algorithms and convergence result are new, and generalize some known results in literature. (C) 2004 Elsevier B.V. All rights reserved.