Dual extremum principles for a homogeneous Dirichlet problem for a parabolic equation.
En la primera parte de este trabajo damos una versión simplificada de la conocida relación entre la dualidad en Programación Semi-Infinita y cierta clase de problemas de momentos, basándonos en las propiedades de los sistemas de Farkas-Minkowski. Planteamos a continuación otra clase de problemas de momentos para cuyo análisis resulta de utilidad una generalización del Lema de Farkas.
The present article explores the way -approximated method is applied to substantiate duality results for the fractional variational problems under invexity. -approximated dual pair is engineered and a careful study of the original dual pair has been done to establish the duality results for original problems. Moreover, an appropriate example is constructed based on which we can validate the established dual statements. The paper includes several recent results as special cases.
We study a quasiconvex conjugation that transforms the level sum of functions into the pointwise sum of their conjugates and derive new duality results for the minimization of the max of two quasiconvex functions. Following Barron and al., we show that the level sum provides quasiconvex viscosity solutions for Hamilton-Jacobi equations in which the initial condition is a general continuous quasiconvex function which is not necessarily Lipschitz or bounded.
2000 Mathematics Subject Classification: 90C48, 49N15, 90C25In this paper we reconsider a nonconvex duality theory established by B. Lemaire and M. Volle (see [4]), related to a primal problem of minimizing the difference of two convex functions subject to a DC-constraint. The purpose of this note is to present a new method based on Toland-Singer duality principle. Applications to the case when the constraints are vector-valued are provided.
Duality of linear programming is used to establish an important duality theorem for a class of non-linear programming problems. Primal problem has quasimonotonic objective function and a convex polyhedron as its constraint set.