Titlebook: Variational Analysis and Generalized Differentiation I; Basic Theory Boris S. Mordukhovich Book 2006 Springer-Verlag Berlin Heidelberg 2006

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Generalized Differentiation in Banach Spacesom the proofs). Developing a . to generalized differentiation, we start with . to sets (Sect.?1.1), then proceed to . of set-valued mappings (Sect.?1.2), and then to . of extended-real-valued functions (Sect.?1.3).

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Generalized Differentiation in Banach Spacesst properties presented in this chapter hold in . Banach spaces (some of them don’t require completeness or even a normed structure, as one can see from the proofs). Developing a . to generalized differentiation, we start with . to sets (Sect.?1.1), then proceed to . of set-valued mappings (Sect.?1.

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Extremal Principle in Variational Analysisions. Actually the whole convex analysis revolves around using separation theorems for convex sets. In problems with nonconvex data separation theorems are applied to convex approximations. This is a conventional way to derive necessary optimality conditions in constrained optimization: first build

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