ENGLISH

Foundations of Mathematical Optimization: Convex Analysis without Linearity

By Diethard Pallaschke , Stefan Rolewicz (auth.)

Book information

Publisher
Springer Netherlands
Year
1997
ISBN
978-90-481-4800-4, 978-94-017-1588-1
DOI
10.1007/978-94-017-1588-1
Language
english
Format
PDF
Filesize
22 MB (23315395 bytes)
Series
Mathematics and Its Applications 388
Edition
1
Pages
585\596
Orientation
yes
Scanned
yes
Time added
2013-08-01 04:00:00
Optimization

Description

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.

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