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Abstract

In this study, we examine Fritz John (FJ) and Karush-Kuhn-Tucker (KKT) type optimality conditions for a class of nonsmooth and nonconvex optimization problems with inequality constraints, where the objective and constraint functions all are assumed to be radially epidifferentiable. The concept of the radial epiderivative constitutes a distinct generalization of classical derivative notions, as it replaces the conventional limit operation with an infimum-based construction. This formulation permits the analysis of directional behavior without invoking standard neighborhood-based assumptions and constructions commonly required in generalized differentiation. This leads to one of the key advantages of the radial epiderivative which lies in its applicability even to discrete domains, where classical and generalized derivatives are often inapplicable or undefined. The other advantage of this concept is that it provides a possibility to inverstigate KKT conditions for global minimums. Consequently, this approach necessitates a reformulation of fundamental analytical tools such as gradient vectors, feasible direction sets, constraint qualifications and other concepts which are central to the derivation of optimality conditions in smooth optimization theory. The primary contribution of this paper is the development of a comprehensive theoretical framework for KKT conditions tailored to the radially epidifferentiable setting. We introduce novel definitions of the radial gradient vector, of the set of feasible directions, and examine how classical constraint qualifications may be interpreted and extended within this new framework.