Practical Augmented Lagrangian Methods for Constrained Optimization

Augmented Lagrangian techniques for the solution of practical constrained optimization problems are the focus of this book, which gives a thorough account of both theory and applications. The authors rigorously delineate mathematical convergence theory based on sequential optimality conditions and novel constraint qualifications. They also orient the book to practitioners by prioritizing results that provide insight on the practical behavior of algorithms and by providing geometrical and algorithmic interpretations of every mathematical result. In addition, they fully describe a freely available computational package for constrained optimization and illustrate its usefulness with applications. This 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.

• A rigorous treatment of convergence theory based on sequential optimality conditions and novel constraint qualifications
• Algorithmic interpretations of mathematical results are emphasised
• The book gives a full description of a freely available computational package for constrained optimization and illustrates its usefulness with applications