Sufficient conditions and duality for multiobjective variational problems with generalized B-invexity
Sufficient conditions of optimality for multiobjective optimization problems with γ-paraconvex data
We study multiobjective optimization problems with γ-paraconvex multifunction data. Sufficient optimality conditions for unconstrained and constrained problems are given in terms of contingent derivatives.
Sufficient Second Order Optimality Conditions for C^1 Multiobjective Optimization Problems
2000 Mathematics Subject Classification: Primary 90C29; Secondary 90C30.In this work, we use the notion of Approximate Hessian introduced by Jeyakumar and Luc [19], and a special scalarization to establish sufficient optimality conditions for constrained multiobjective optimization problems. Throughout this paper, the data are assumed to be of class C^1, but not necessarily of class C^(1.1).
Support separation theorems and their applications to vector surrogate reverse duality
Sur la dualité en optimisation vectorielle convexe
Sur la propriété de domination et l'existence de points Pareto-efficaces en optimisation vectorielle convexe
Symmetric duality for a class of multiobjective programming.