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The third edition of the book is a thoroughly rewritten version of the 1999 2nd edition. New material was included, some of the old material was discarded, and a large portion of the remainder was reorganized or revised. This book provides a comprehensive and accessible presentation of algorithms for solving continuous optimization problems. It relies on rigorous mathematical analysis, but also aims at an intuitive exposition that makes use of visualization where possible. It places particular emphasis on modern developments, and their widespread applications in fields such as large-scale resource allocation problems, signal processing, and machine learning. The book was developed through instruction at MIT, focuses on nonlinear and other types of optimization: iterative algorithms for constrained and unconstrained optimization, Lagrange multipliers and duality, large scale problems, and the interface between continuous and discrete optimization. Among its special features, the book: 1) provides extensive coverage of iterative optimization methods within a unifying framework 2) provides a detailed treatment of interior point methods for linear programming 3) covers in depth duality theory from both a variational and a geometrical/convex analysis point of view 4) includes much new material on a number of topics, such as neural network training, large-scale optimization, signal processing, machine learning, and optimal control 5) includes a large number of examples and exercises detailed solutions of many of which are posted on the internet.
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Previews available in: English
Edition | Availability |
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1
Nonlinear Programming: 3rd Edition
Jun 27, 2016, Athena Scientific
hardcover
in English
1886529051 9781886529052
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2
Nonlinear Programming
September 1, 1999, Athena Scientific
Hardcover
in English
- 2nd edition
1886529000 9781886529007
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3 |
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Book Details
Edition Notes
Source title: Nonlinear Programming: 3rd Edition
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This book develops in depths nonlinear programming, a central algorithmic method for optimization. The treatment focuses on constrained and unconstrained iterative algorithms, Lagrange multiplier theory, and large scale optimization methods.
--back cover
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- Created April 26, 2022
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May 19, 2025 | Edited by MARC Bot | import existing book |
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