A class of generalized best approximation problems in locally convex linear topological spaces.
A critical point result for non-differentiable indefinite functionals
In this paper, two deformation lemmas concerning a family of indefinite, non necessarily continuously differentiable functionals are proved. A critical point theorem, which extends the classical result of Benci-Rabinowitz [14, Theorem 5.29] to the above-mentioned setting, is then deduced.
A disjunctive linear fractional max-min problem
A further generalization of Ky Fan's maximal inequality and its applications
A general mountain pass principle for locating and classifying critical points
A minimax formula for the principal eigenvalues of Dirichlet problems and its applications.
A minimax inequality with applications to existence of equilibrium point and fixed point theorems
Ky Fan’s minimax inequality [8, Theorem 1] has become a versatile tool in nonlinear and convex analysis. In this paper, we shall first obtain a minimax inequality which generalizes those generalizations of Ky Fan’s minimax inequality due to Allen [1], Yen [18], Tan [16], Bae Kim Tan [3] and Fan himself [9]. Several equivalent forms are then formulated and one of them, the maximal element version, is used to obtain a fixed point theorem which in turn is applied to obtain an existence theorem of an...
A min-max theorem and its applications to nonconservative systems.
A min-max theorem for multiple integrals of the Calculus of Variations and applications
In this paper we deal with the existence of critical points for functionals defined on the Sobolev space by , , where is a bounded, open subset of . Since the differentiability can fail even for very simple examples of functionals defined through multiple integrals of Calculus of Variations, we give a suitable version of the Ambrosetti-Rabinowitz Mountain Pass Theorem, which enables us to the study of critical points for functionals which are not differentiable in all directions. Then we...
A priori bounds and renormalized Morse indices of solutions of an elliptic system
A simple proof of the minimax-theorem
A variationally consistent generalized variable formulation of the elastoplastic rate problem
The elastoplastic rate problem is formulated as an unconstrained saddle point problem which, in turn, is obtained by the Lagrange multiplier method from a kinematic minimum principle. The finite element discretization and the enforcement of the min-max conditions for the Lagrangean function lead to a set of algebraic governing relations (equilibrium, compatibility and constitutive law). It is shown how important properties of the continuum problem (like, e.g., symmetry, convexity, normality) carry...
An Elliptic Neumann Problem with Subcritical Nonlinearity
We establish the existence of a solution to the Neumann problem in the half-space with a subcritical nonlinearity on the boundary. Solutions are obtained through the constrained minimization or minimax. The existence of solutions depends on the shape of a boundary coefficient.
An extension of Fan's fixed point theorem and equilibrium point of an abstract economy
An ill-posed nonlocal two-point problem for systems of partial differential equations.
An implementation of recursive quadratic programming variable metric methods for linearly constrained nonlinear minimax approximation
Analyse des problèmes de forme par la dérivation des minimax
Asignación de recursos Max-Min: propiedades y algoritmos.
Este trabajo trata el problema de asignación de recursos cuando el objetivo es maximizar la mínima recompensa y las funciones recompensa son continuas y estrictamente crecientes. Se estudian diferentes propiedades que conducen a algoritmos que permiten de forma eficiente la resolución de gran variedad de problemas de esta naturaleza, tanto con variables continuas como discretas.
Asymptotically Linear Elliptic Boundary Value Problems.
Augmented Lagrangian methods for variational inequality problems
We introduce augmented Lagrangian methods for solving finite dimensional variational inequality problems whose feasible sets are defined by convex inequalities, generalizing the proximal augmented Lagrangian method for constrained optimization. At each iteration, primal variables are updated by solving an unconstrained variational inequality problem, and then dual variables are updated through a closed formula. A full convergence analysis is provided, allowing for inexact solution of the subproblems. ...