Nonlinear Programming: Analysis and Methods

Nonlinear Programming: Analysis and Methods

by Mordecai Avriel
Nonlinear Programming: Analysis and Methods

Nonlinear Programming: Analysis and Methods

by Mordecai Avriel

eBook

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Overview

Comprehensive and complete, this overview provides a single-volume treatment of key algorithms and theories. The author provides clear explanations of all theoretical aspects, with rigorous proof of most results. The two-part treatment begins with the derivation of optimality conditions and discussions of convex programming, duality, generalized convexity, and analysis of selected nonlinear programs. The second part concerns techniques for numerical solutions and unconstrained optimization methods, and it presents commonly used algorithms for constrained nonlinear optimization problems. This graduate-level text requires no advanced mathematical background beyond elementary calculus, linear algebra, and real analysis. 1976 edition. 58 figures. 7 tables.

Product Details

ISBN-13: 9780486151670
Publisher: Dover Publications
Publication date: 08/15/2012
Series: Dover Books on Computer Science
Sold by: Barnes & Noble
Format: eBook
Pages: 528
File size: 32 MB
Note: This product may take a few minutes to download.

Table of Contents

Author's Preface to the Dover Edition
1. Introduction
II. Analysis
2. Classical Optimization--Unconstrained and Equality Constrained Problems
3. Optimality Conditions for Constrained Extrema
4. Convex Sets and Functions
5. Duality in Nonlinear Convex Programming
6. Generalized Convexity
7. Analysis of Selected Nonlinear Programming Problems
II. Methods
8. One-Dimensional Optimization
9. Multidimensional Unconstrained Optimization Without Derivatives: Empirical and Conjugate Direction Methods
10. Second Derivative, Steepest Descent and Conjugate Gradient Methods
11. Variable Metric Algorithms
12. Penalty Function Methods
13. Solution of Constrained Problems by Extensions of Unconstrained Optimization Techniques
14. Approximation-Type Algorithms
Author Index. Subject Index.
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