Numerical Optimization

Numerical Optimization presents a comprehensive and up-to-date description of the most effective methods in continuous optimization. It responds to the growing interest in optimization in engineering, science, and business by focusing on the methods that are best suited to practical problems. For th...

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Bibliographic Details
Main Authors: Nocedal, Jorge (Author), Wright, Stephen J. (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: New York, NY : Springer New York, 2006.
Edition:Second Edition.
Series:Springer Series in Operations Research and Financial Engineering,
Subjects:
Online Access:Full Text via HEAL-Link
Table of Contents:
  • Fundamentals of Unconstrained Optimization
  • Line Search Methods
  • Trust-Region Methods
  • Conjugate Gradient Methods
  • Quasi-Newton Methods
  • Large-Scale Unconstrained Optimization
  • Calculating Derivatives
  • Derivative-Free Optimization
  • 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 and Augmented Lagrangian Methods
  • Sequential Quadratic Programming
  • Interior-Point Methods for Nonlinear Programming.