Ebook: Practical augmented Lagrangian methods for constrained optimization
- Genre: Mathematics // Optimization. Operations Research
- Tags: Математика, Методы оптимизации
- Series: Fundamentals of Algorithms
- Year: 2014
- Publisher: Society for Industrial & Applied Mathematics
- Language: English
- pdf
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.
Contents: Chapter 1: Introduction ; Chapter 2: Practical Motivations; Chapter 3: Optimality Conditions; Chapter 4: Model Augmented Lagrangian Algorithm; Chapter 5: Global Minimization Approach; Chapter 6: General Affordable Algorithms; Chapter 7: Boundedness of the Penalty Parameters; Chapter 8: Solving Unconstrained Subproblems; Chapter 9: Solving Constrained Subproblems; Chapter 10: First Approach to Algencan; Chapter 11: Adequate Choice of Subroutines; Chapter 12: Making a Good Choice of Algorithmic Options and Parameters; Chapter 13: Practical Examples; Chapter 14: Final Remarks