Lectures on Modern Convex Optimization
Analysis, Algorithms, and Engineering Applications
$173.00 (P)
Part of MPS-SIAM Series on Optimization
- Authors:
- Aharon Ben-Tal, Technion - Israel Institute of Technology, Haifa
- Arkadi Nemirovski, Technion - Israel Institute of Technology, Haifa
- Date Published: January 1987
- availability: This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.
- format: Paperback
- isbn: 9780898714913
$
173.00
(P)
Paperback
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Here is a book devoted to well-structured and thus efficiently solvable convex optimization problems, with emphasis on conic quadratic and semidefinite programming. The authors present the basic theory underlying these problems as well as their numerous applications in engineering, including synthesis of filters, Lyapunov stability analysis, and structural design. The authors also discuss the complexity issues and provide an overview of the basic theory of state-of-the-art polynomial time interior point methods for linear, conic quadratic, and semidefinite programming. The book's focus on well-structured convex problems in conic form allows for unified theoretical and algorithmical treatment of a wide spectrum of important optimization problems arising in applications.
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×Product details
- Date Published: January 1987
- format: Paperback
- isbn: 9780898714913
- length: 504 pages
- dimensions: 254 x 178 x 25 mm
- weight: 0.864kg
- availability: This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.
Table of Contents
Preface
Lecture 1. Linear Programming
Lecture 2. From Linear Programming to Conic Programming
Lecture 3. Conic Quadratic Programming
Lecture 4. Semidefinite Programming
Lecture 5. Computational Tractability of Convex Programs
Lecture 6. Interior Point Polynomial Time Methods for Linear Programming, Conic Quadratic Programming, and Semidefinite Programming
Solutions to Selected Exercises
Index.
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