On duality for nonconvex minimization problems within the framework of abstract convexity

By applying the perturbation function approach, we propose the Lagrangian and the conjugate duals for minimization problems of the sum of two, generally nonconvex, functions. The main tools are the $\mathrm{\Phi }$-convexity theory and minimax theorems for $\mathrm{\Phi }$-convex functions. We provide conditions ensuring zero duality gap and introduce $\mathrm{\Phi }$-Karush-Kuhn-Tucker conditions that characterize solutions to primal and dual problems. We also discuss the relationship between the dual problems introduced in the present investigation and some conjugate-type duals existing in the literature.