Introduction to Nonlinear Optimization - Theory, Algorithms, and Applications with MATLAB

This book provides the foundations of the theory of nonlinear optimization as well as some related algorithms and presents a variety of applications from diverse areas of applied sciences. The author combines three pillars of optimization - theoretical and algorithmic foundation, familiarity with va...

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Bibliographic Details
Main Author Beck, Amir
Format eBook Book
LanguageEnglish
Published Philadelphia Society for Industrial and Applied Mathematics (SIAM) 2014
Mathematical Optimization Society
Society for Industrial and Applied Mathematics
Society for Industrial and Applied Mathematics (SIAM, 3600 Market Street, Floor 6, Philadelphia, PA 19104)
SeriesMOS-SIAM series on optimization
Subjects
Control Theory & Optimization
Convex analysis
Matematical optimization
Mathematical optimization
MATLAB
Nonlinear optimization
Nonlinear theories
Optimality conditions
Process Design, Control & Automation
Scientific computing
Smooth optimization algorithms
Online AccessGet full text
ISBN1611973643
9781611973648
DOI10.1137/1.9781611973655

Cover

Table of Contents:
  • Title Page Preface Table of Contents 1. Mathematical Preliminaries 2. Optimality Conditions for Unconstrained Optimization 3. Least Squares 4. The Gradient Method 5. Newton's Method 6. Convex Sets 7. Convex Functions 8. Convex Optimization 9. Optimization over a Convex Set 10. Optimality Conditions for Linearly Constrained Problems 11. The KKT Conditions 12. Duality Bibliographic Notes Bibliography Index
  • Mathematical preliminaries -- Optimality conditions for unconstrained optimization -- Least squares -- The gradient method -- Newton's method -- Convex sets -- Convex functions -- Convex optimization -- Optimization over a convex set -- Optimality conditions for linearly constrained problems -- The KKT conditions -- Duality.