$ V $-$ E $-invexity in $ E $-differentiable multiobjective programming

<p style='text-indent:20px;'>In this paper, a new concept of generalized convexity is introduced for not necessarily differentiable vector optimization problems with <inline-formula><tex-math id="M4">\begin{document}$ E $\end{document}</tex-math></inline-formula>-differentiable functions. Namely, an id="M5">\begin{document}$ vector-valued function, the id="M6">\begin{document}$ V $\end{document}</tex-math></inline-formula>-<inline-formula><tex-math id="M7">\begin{document}$ $\end{document}</tex-math></inline-formula>-invexity defined as generalization id="M8">\begin{document}$ id="M9">\begin{document}$ notion and id="M10">\begin{document}$ $\end{document}</tex-math></inline-formula>-invexity. Further, sufficiency so-called id="M11">\begin{document}$ $\end{document}</tex-math></inline-formula>-Karush-Kuhn-Tucker optimality conditions are established considered id="M12">\begin{document}$ both inequality equality constraints under id="M13">\begin{document}$ id="M14">\begin{document}$ hypotheses. Furthermore, id="M15">\begin{document}$ $\end{document}</tex-math></inline-formula>-dual problem in sense Mond-Weir id="M16">\begin{document}$ multiobjective programming several id="M17">\begin{document}$ $\end{document}</tex-math></inline-formula>-duality theorems derived also appropriate id="M18">\begin{document}$ id="M19">\begin{document}$ assumptions.</p>