Auxiliary problem principle extended to variational inequalities
Journal of Optimization Theory and Applications
Mathematical Programming: Series A and B
Mathematical Programming: Series A and B
General algorithm for variational inequalities
Journal of Optimization Theory and Applications
Nonconvex functions and variational inequalities
Journal of Optimization Theory and Applications
Interative schemes for solving mixed variational-like inequalites1,2
Journal of Optimization Theory and Applications
A new class of completely generalized quasi-variational inclusions in Banach spaces
Journal of Computational and Applied Mathematics
Journal of Computational and Applied Mathematics
Computers & Mathematics with Applications
Computers & Mathematics with Applications
Iterative algorithm for finding approximate solutions of mixed quasi-variational-like inclusions
Computers & Mathematics with Applications
General iterative algorithms for solving mixed quasi-variational-like inclusions
Computers & Mathematics with Applications
Generalized mixed variational-like inequality for random fuzzy mappings
Journal of Computational and Applied Mathematics
Existence and algorithm of solutions for mixed quasi-variational-like inclusions in Banach spaces
Computers & Mathematics with Applications
Journal of Computational and Applied Mathematics
Journal of Computational and Applied Mathematics
Existence and algorithms for bilevel generalized mixed equilibrium problems in Banach spaces
Journal of Global Optimization
Hi-index | 7.30 |
In this paper, we study a new class of nonlinear mixed variational-like inequalities in reflexive Banach spaces. By applying a minimax inequality due to author, we first prove an existence uniqueness theorem of solutions for the nonlinear mixed variational-like inequalities. Next, we extend the auxiliary problem technique under reflexive Banach space setting to suggest and analyze an innovative iterative algorithm to compute the approximate solutions of the nonlinear mixed variational-like inequalities. The convergence criteria of the iterative algorithm is also given. These results improve and generalize many known results in recent literature.