Numerical Optimization
This is a book for people interested in solving optimization problems. Because of the wide (and growing) use of optimization in science, engineering, economics, and industry, it is essential for students and practitioners alike to develop an understanding of optimization algorithms. Knowledge of the...
Corporate Author: | |
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Other Authors: | , |
Format: | Electronic eBook |
Language: | English |
Published: |
New York, NY :
Springer New York,
1999.
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Series: | Springer Series in Operations Research and Financial Engineering,
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Subjects: | |
Online Access: | Full Text via HEAL-Link |
Table of Contents:
- Fundamentals of Unconstrained Optimization
- Line Search Methods
- Trust-Region Methods
- Conjugate Gradient Methods
- Practical Newton Methods
- Calculating Derivatives
- Quasi-Newton Methods
- Large-Scale Quasi-Newton and Partially Separable Optimization
- Nonlinear Least-Squares Problems
- Nonlinear Equations
- Theory of Constrained Optimization
- Linear Programming: The Simplex Method
- Linear Programming: Interior-Point Methods
- Fundamentals of Algorithms for Nonlinear Constrained Optimization
- Quadratic Programming
- Penalty, Barrier, and Augmented Lagrangian Methods
- Sequential Quadratic Programming.