Optimality Conditions in Quasidifferentiable Vector Optimization
研究了带不等式约束的拟可微向量优化问题，推导了弱Pareto解的Fritz John型和Karush-Kuhn-Tucker型必要最优性条件，并在拟可微F-凸假设下建立了充分最优性条件。
In the paper, the quasidifferentiable vector optimization problem with the inequality constraints is considered. The Fritz John-type necessary optimality conditions and the Karush–Kuhn–Tucker-type necessary optimality conditions for a weak Pareto solution are derived for such a nonsmooth vector optimization problem. Further, the concept of an F-convex function with respect to a convex compact set is introduced. Then, the sufficient optimality conditions for a (weak) Pareto optimality of a feasible solution are established for the considered nonsmooth multiobjective optimization problem under assumptions that the involved functions are quasidifferentiable F-convex with respect to convex compact sets which are equal to Minkowski sum of their subdifferentials and superdifferentials at this point.