Recent studies have used Karush-Kuhn-Tucker (KKT) optimality conditions to develop a KKT ProximityMeasure (KKTPM) for terminating amulti-objective optimization simulation run based on theoretical convergence of solutions. In addition to determining a suitable termination condition and due to their ability to provide a single measure for convergence to Pareto-optimal solutions, the developed KKT...

To achieve perfect secrecy in a multiple-input multiple-output (MIMO) Gaussian wiretap channel (WTC), we need to find its capacity and optimal signaling, which involves solving difference of convex functions program known be non-convex for the non-degraded case. deal with this, class existing solutions have been developed but only local optimality is guaranteed by standard convergence analysis....

We analyze the performance of the Minimal Residual Method applied to linear Karush-Kuhn-Tucker systems arising in connection with inverse problems. Such optimality systems typically have a saddle point structure and have unique solutions for all α > 0, where α is the parameter employed in the Tikhonov regularization. Unfortunately, the associated spectral condition number is very large for smal...

In the traditional nonlinear optimization theory, Karush-Kuhn-Tucker (KKT) optimality conditions for constrained problems with inequality constraints play an essential role. The situation becomes challenging when theory of is discussed under uncertainty. Several researchers have interval approach to tackle uncertainty and derived conditions. However, there are several realistic situations in wh...

Recently, Yamanaka and Yamashita proposed the so-called positively homogeneous optimization problem, which includes many important problems, such as absolute-value gauge problems. They presented a closed form of dual formulation for showed weak duality equivalence to Lagrangian under some conditions. In this work, we focus on special whose objective function constraints consist linear functions...

This paper is concerned with the study of duality conditions to convex-concave generalized multiobjective fuzzy nonlinear fractional disjunctive programming problems for which the decision set is the union of a family of convex sets. The Lagrangian function for such problems is defined and the Kuhn-Tucker Saddle and Stationary points are characterized. In addition, some important theorems relat...