We consider the classical Markowitz portfolio optimization problem with additional constraints representing so-called short sales.  The two objectives of this multiobjective problem are the expected return and the variance of a portfolio combined by a number of risky securities. A...

We consider the classical Markowitz portfolio optimization problem with additional constraints representing so-called short sales.  The two objectives of this multiobjective problem are the expected return and the variance of a portfolio combined by a number of risky securities. A...

For an optimization problem with a composed objective function and composed constraint functions we determine, by means of the conjugacy approach based on the perturbation theory, some dual problems to it. The relations between the optimal objective values of these duals are studied. Moreover,...

A multiobjective programming problem characterized by convex goal functions and linear inequality constraints is studied. The investigation aims to the construction of a multiobjective dual problem permitting the verification of strong duality as well as optimality conditions.  For the...

A general duality framework in convex multiobjective optimization is established using the scalarization with K-strongly increasing functions and the conjugate duality for composed convex cone-constrained optimization problems. Other scalarizations used in the literature arise as particular...

For an optimization problem with a composed objective function and composed constraint functions we determine, by means of the conjugacy approach based on the perturbation theory, some dual problems to it. The relations between the optimal objective values of these duals are studied. Moreover,...

In this paper, we deal with the construction of gap functions for variational inequalities by using an approach which bases on the conjugate duality. Under certain assumptions we also investigate a further class of gap functions for the variational inequality problem, the so-called dual gap...