Nonsmooth Analysis [Paperback]

This book treats various concepts of generalized derivatives and subdifferentials in normed spaces, their geometric counterparts and their application to optimization problems. It starts with the subdifferential of convex analysis, passes to corresponding concepts for locally Lipschitz continuous functions and then presents subdifferentials for general lower semicontinuous functions. All basic tools are presented where they are needed: this concerns separation theorems, variational and extremal principles as well as relevant parts of multifunction theory. Each chapter ends with bibliographic notes and exercises.

This book treats various concepts of generalized derivatives and subdifferentials in normed spaces, their geometric counterparts and their application to optimization problems. The presentation is rigorous, with detailed proofs.

Preliminaries.- The Conjugate of Convex Functionals.- Classical Derivatives.- The Subdifferential of Convex Functionals.- Optimality Conditions for Convex Problems.- Duality of Convex Problems.- Derivatives and Subdifferentials of Lipschitz Functionals.- Variational Principles.- Subdifferentials of Lower Semicontinuous Functionals.- Multifunctions.- Tangent and Normal Cones.- Optimality Conditions for Nonconvex Problems.- Extremal Principles and More Normals and Subdifferentials.

From the reviews:

The main idea of the presented monograph is to deal with extremum problems connected with non-differentiable data. The text is divided into 13 chapters with an Appendix and 229 references. Each chapter ends with recommended references and exercises. & The text contains a big amount of latest results achieved in nonsmooth analysis together with applications in optimization. It can be recommended both to graduate students and the researchers in applied mathematics and optimization. (Igor Bock, Zentralblatt MATH, Vol. 1120 (22), 2007)

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