In this paper, proper optimality concepts in vector optimization with variable ordering
structures are introduced for the first time and characterization results via scalarizations are …

In this paper, we study the radial epiderivative notion for nonconvex functions, which
extends the (classical) directional derivative concept. The paper presents new definition and …

This paper presents a weak subgradient based method for solving nonconvex optimization
problems. The method uses a weak subgradient of the objective function at a current point to …

In this paper, a novel sharp Augmented Lagrangian-based global optimization method is
developed for solving constrained non-convex optimization problems. The algorithm …

In this paper, zero duality gap conditions in nonconvex optimization are investigated. It is
considered that dual problems can be constructed with respect to the weak conjugate …

In this paper, we study some characterizations of the class of weakly subdifferentiable
functions and formulate optimality conditions for nonconvex mathematical programming …

This paper presents a robust binary classification method, which is an extended version of
the Modified Polyhedral Conic Functions (M-PCF) algorithm, earlier developed by Gasimov …

We study a new version of the weak subgradient method, recently developed by Dinc Yalcin
and Kasimbeyli for solving nonsmooth, nonconvex problems. This method is based on the …

The aim of this paper is to present separation theorems for two disjoint closed sets, without
convexity condition. First, a separation theorem for a given closed cone and a point outside …

This paper is concerned with optimality conditions for a class of nonsmooth fuzzy
optimization problems based on gH-weak subdifferentiability. To this end, we first define the …