Foundations of Mathematical Optimization - Convex Analysis without Linearity (Paperback, Softcover reprint of hardcover 1st ed. 1997)

Many books on optimization consider only finite dimensional spaces. This volume is unique in its emphasis: the first three chapters develop optimization in spaces without linear structure, and the analog of convex analysis is constructed for this case. Many new results have been proved specially for this publication. In the following chapters optimization in infinite topological and normed vector spaces is considered. The novelty consists in using the drop property for weak well-posedness of linear problems in Banach spaces and in a unified approach (by means of the Dolecki approximation) to necessary conditions of optimality. The method of reduction of constraints for sufficient conditions of optimality is presented. The book contains an introduction to non-differentiable and vector optimization. Audience: This volume will be of interest to mathematicians, engineers, and economists working in mathematical optimization.

General

Imprint:	Springer
Country of origin:	Netherlands
Series:	Mathematics and Its Applications, 388
Release date:	December 2010
First published:	1997
Authors:	Diethard Ernst Pallaschke • S. Rolewicz
Dimensions:	235 x 155 x 30mm (L x W x T)
Format:	Paperback
Pages:	585
Edition:	Softcover reprint of hardcover 1st ed. 1997
ISBN-13:	978-90-481-4800-4
Categories:	Books > Science & Mathematics > Mathematics > Optimization > General Promotions
LSN:	90-481-4800-6
Barcode:	9789048148004

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