On approximate solutions for nonsmooth robust multiobjective optimization problems

We introduce a new concept of generalized convexity of 'degree n' for a multiobjective optimization problem and is compared it to the previous notions of generalized convex functions. Some examples to justify the importance of the term 'degree n' are provided. Namely, the conclusions of our results may fail if this term is dropped. By applying our new definition to nonsmooth robust multiobjective optimization problems, we establish the nonsmooth robust optimality conditions and robust duality theory for robust epsilon-quasi-(weakly) efficient solutions. A robust epsilon-Mond-Weir type duality of degree n for an uncertain multi-objective optimization problem under our generalized convexity assumption is presented. Furthermore, we introduce an epsilon-approximate scalar saddle-point and an epsilon-approximate weak vector saddle-point of degree n for the robust multi-objective optimization problem. The relationships between these two concepts with robust epsilon-approximate (KKT) condition and robust epsilon-weakly efficient solutions are also given.