Totally Convex Functions for Fixed Points Computation and Infinite Dimensional Optimization (Hardcover)

The main purpose of this book is to present, in a unified approach, several algorithms for fixed point computation, convex feasibility and convex optimization in infinite dimensional Banach spaces, and for problems involving, eventually, infinitely many constraints. For instance, methods like the simultaneous projection algorithm for feasibility, the proximal point algorithm and the augmented Lagrangian algorithm are rigorously formulated and analyzed in this general setting and shown to be applicable to much wider classes of problems than previously known. For this purpose, a new basic concept, "total convexity", is introduced. Its properties are deeply explored, and a comprehensive theory is presented, bringing together previously unrelated ideas from Banach space geometry, finite dimensional convex optimization and functional analysis. For making a general approach possible the work aims to improve upon classical results like the Holder-Minkowsky inequality of p. This book should be of interest to both researchers in nonlinear analysis and to applied mathematicians dealing with numerical solution of integral equations, equilibrium problems, image reconstruction, and optimal control.

General

Imprint:	Kluwer Academic Publishers
Country of origin:	United States
Series:	Applied Optimization, v. 40
Release date:	May 2000
First published:	May 2000
Authors:	Dan Butnariu • Alfredo N. Iusem
Dimensions:	230mm (L)
Format:	Hardcover
Pages:	220
ISBN-13:	978-0-7923-6287-6
Categories:	Books > Science & Mathematics > Mathematics > Calculus & mathematical analysis > Vector & tensor analysis Books > Professional & Technical > Mechanical engineering & materials > Production engineering > General Promotions
LSN:	0-7923-6287-X
Barcode:	9780792362876

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