Convex Analysis and Minimization Algorithms I: Fundamentals

Author:   Jean-Baptiste Hiriart-Urruty ,  Claude Lemarechal
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Edition:   Softcover reprint of hardcover 1st ed. 1993
Volume:   305
ISBN:  

9783642081613


Pages:   418
Publication Date:   15 May 2011
Format:   Paperback
Availability:   Out of print, replaced by POD   Availability explained
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Convex Analysis and Minimization Algorithms I: Fundamentals


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Overview

Convex Analysis may be considered as a refinement of standard calculus, with equalities and approximations replaced by inequalities. As such, it can easily be integrated into a graduate study curriculum. Minimization algorithms, more specifically those adapted to non-differentiable functions, provide an immediate application of convex analysis to various fields related to optimization and operations research. These two topics making up the title of the book, reflect the two origins of the authors, who belong respectively to the academic world and to that of applications. Part I can be used as an introductory textbook (as a basis for courses, or for self-study); Part II continues this at a higher technical level and is addressed more to specialists, collecting results that so far have not appeared in books.

Full Product Details

Author:   Jean-Baptiste Hiriart-Urruty ,  Claude Lemarechal
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Edition:   Softcover reprint of hardcover 1st ed. 1993
Volume:   305
Dimensions:   Width: 15.50cm , Height: 2.20cm , Length: 23.50cm
Weight:   0.670kg
ISBN:  

9783642081613


ISBN 10:   3642081614
Pages:   418
Publication Date:   15 May 2011
Audience:   Professional and scholarly ,  Professional and scholarly ,  Professional & Vocational ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Out of print, replaced by POD   Availability explained
We will order this item for you from a manufatured on demand supplier.

Table of Contents

Table of Contents Part I.- I. Convex Functions of One Real Variable.- II. Introduction to Optimization Algorithms.- III. Convex Sets.- IV. Convex Functions of Several Variables.- V. Sublinearity and Support Functions.- VI. Subdifferentials of Finite Convex Functions.- VII. Constrained Convex Minimization Problems: Minimality Conditions, Elements of Duality Theory.- VIII. Descent Theory for Convex Minimization: The Case of Complete Information.- Appendix: Notations.- 1 Some Facts About Optimization.- 2 The Set of Extended Real Numbers.- 3 Linear and Bilinear Algebra.- 4 Differentiation in a Euclidean Space.- 5 Set-Valued Analysis.- 6 A Bird’s Eye View of Measure Theory and Integration.- Bibliographical Comments.- References.

Reviews

From the reviews: ... The book is very well written, nicely illustrated, and clearly understandable even for senior undergraduate students of mathematics... Throughout the book, the authors carefully follow the recommendation by A. Einstein: 'Everything should be made as simple as possible, but not simpler.'


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