Minimax fractional programming under nonsmooth generalized (F,ρ,θ)-d-univexity

In this paper, we are concerned with a nondifferentiable minimax fractional problem with inequality constraints. We introduce a new class of generalized convex function, that is, nonsmooth generalized (F,ρ,θ)-d-univex function. In the framework of the new concept, we derive Kuhn–Tucker type sufficient optimality conditions and establish weak, strong and converse duality theorems for the problem and its three different types of dual problems.