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The Fermat rule for set optimization problems with Lipschitzian set-valued mappings. (English) Zbl 1460.90141

Summary: In this paper, we consider set optimization problems where the solution concept is given by the set approach. Specifically, we deal with the lower less and the upper less set relations. First, we derive the convexity and Lipschitzianity of suitable scalarizing functions under the assumption that the set-valued objective mapping has certain convexity and Lipschitzianity properties. Then, we obtain upper estimates of the limiting subdifferential of these functionals. These results, together with the properties of the scalarization functions, allow us to obtain a Fermat rule for set optimization problems with Lipschitzian data.

MSC:

90C26 Nonconvex programming, global optimization
65K10 Numerical optimization and variational techniques
90C30 Nonlinear programming
90C29 Multi-objective and goal programming