Society for Industrial and Applied Mathematics eBooks· 2014· Book chapter
Practical Augmented Lagrangian Methods for Constrained Optimization
- 438citations
- 2014year
Short summary
This book presents Augmented Lagrangian methods for solving practical constrained optimization problems, emphasizing convergence theory and practical algorithmic behavior.
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Key points
- Focuses on Augmented Lagrangian methods for practical constrained optimization.
- Delineates mathematical convergence theory using sequential optimality conditions and novel constraint qualifications.
- Provides geometrical and algorithmic interpretations of mathematical results.
- Includes a freely available computational package with applications.
AI-generated from the title and abstract; the full text is not read.
Abstract
This book focuses on Augmented Lagrangian techniques for solving practical constrained optimization problems. The authors rigorously delineate mathematical convergence theory based on sequential optimality conditions and novel constraint qualifications. They also orient the book to practitioners by giving priority to results that provide insight on the practical behavior of algorithms and by providing geometrical and algorithmic interpretations of every mathematical result, and they fully describe a freely available computational package for constrained optimization and illustrate its usefulness with applications. Audience: The book is aimed at engineers, physicists, chemists, and other practitioners interested in full access to comprehensive and well-documented software for large-scale optimization as well as up-to-date convergence theory and its practical consequences. It will also be of interest to graduate and advanced undergraduate students in mathematics, computer science, applied mathematics, optimization, and numerical analysis.
The authors' abstract, as published at the source. Society for Industrial and Applied Mathematics eBooks, 2014 · DOI ↗
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Field: Numerical Analysis
Numerical AnalysisMathematics