PRACTICAL OPTIMIZATION: Algorithms and Engineering Applications
Chapters
- The Optimization Problem
- Basic Principles
- General Properties of Algorithms
- One-Dimentional Optimization
- Basic Multidimensional Gradient Methods
- Conjugate-Direction Methods
- Quasi-Newton Methods
- Minimax Methods
- Applications of Unconstrained Optimization
- Fundamentals of Constrained Optimization
- Linear Programming Part I - the Simplex Method
- Linear Programming Part II - Interior Point Methods
- Quadratic and Convex Programming
- Semidefinite and Second-Order Cone Programming
- General Nonlinear Optimization Problems
- Applications of Constrained Optimization
Appendices
- Basics of Linear Algebra
- Basics of Digital Filters
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