The first chapter provides some basic definitions and results from the theory of convex analysis and nonlinear mappings related to our work. Some sufficient conditions for the existence of a solution of problem (GVIP) are also recalled. In the second chapter, we first illustrate the scope of the auxiliary problem procedure designed to solve problems like (GVIP) by examining some well-known methods included in that framework. Then, we review the most representative convergence results for that class of methods that can be found in the literature in the case where F is singlevalued as well as in the multivalued case. Finally, we somewhat discuss the particular case of projection methods to solve affine variational inequalities. The third chapter introduces the variational convergence notion of Mosco and combines it with the auxiliary problem principle. Then, we recall the convergence conditions existing for the resulting perturbed scheme before our own contribution and we comment them. Finally, we introduce and illustrate the rate of convergence condition that we impose on the perturbations to obtain better convergence results. Chapter 4 presents global and local convergence results for the family of perturbed methods in the case where F is singlevalued. We also discuss how our results extend or improve the previous ones. Chapter 5 studies the multivalued case. First, we present convergence results generalizing those obtained when there is no perturbations. Then, we relax the scheme by means of a notion of enlargement of an operator and we provide convergence conditions for this inexact scheme. In Chapter 6, we build a bundle algorithm to solve problem (GVIP) and we study its convergence.

This work aims to investigate some applications of the conjugate duality for scalar and vector optimization problems to the construction of gap functions for variational inequalities and equilibrium problems. The basic idea of the approach is to reformulate variational inequalities and equilibrium problems into optimization problems depending on a fixed variable, which allows us to apply duality results from optimization problems. Based on some perturbations, first we consider the conjugate duality for scalar optimization. As applications, duality investigations for the convex partially separable optimization problem are discussed. Afterwards, we concentrate our attention on some applications of conjugate duality for convex optimization problems in finite and infinite-dimensional spaces to the construction of a gap function for variational inequalities and equilibrium problems. To verify the properties in the definition of a gap function weak and strong duality are used. The remainder of this thesis deals with the extension of this approach to vector variational inequalities and vector equilibrium problems. By using the perturbation functions in analogy to the scalar case, different dual problems for vector optimization and duality assertions for these problems are derived. This study allows us to propose some set-valued gap functions for the vector variational inequality. Finally, by applying the Fenchel duality on the basis of weak orderings, some variational principles for vector equilibrium problems are investigated.

This work aims to investigate some applications of the conjugate duality for scalar and vector optimization problems to the construction of gap functions for variational inequalities and equilibrium problems. The basic idea of the approach is to reformulate variational inequalities and equilibrium problems into optimization problems depending on a fixed variable, which allows us to apply duality results from optimization problems. Based on some perturbations, first we consider the conjugate duality for scalar optimization. As applications, duality investigations for the convex partially separable optimization problem are discussed. Afterwards, we concentrate our attention on some applications of conjugate duality for convex optimization problems in finite and infinite-dimensional spaces to the construction of a gap function for variational inequalities and equilibrium problems. To verify the properties in the definition of a gap function weak and strong duality are used. The remainder of this thesis deals with the extension of this approach to vector variational inequalities and vector equilibrium problems. By using the perturbation functions in analogy to the scalar case, different dual problems for vector optimization and duality assertions for these problems are derived. This study allows us to propose some set-valued gap functions for the vector variational inequality. Finally, by applying the Fenchel duality on the basis of weak orderings, some variational principles for vector equilibrium problems are investigated.