PRACTICAL OPTIMIZATION: Algorithms and Engineering Applications


  1. The Optimization Problem
  2. Basic Principles
  3. General Properties of Algorithms
  4. One-Dimentional Optimization
  5. Basic Multidimensional Gradient Methods
  6. Conjugate-Direction Methods
  7. Quasi-Newton Methods
  8. Minimax Methods
  9. Applications of Unconstrained Optimization
  10. Fundamentals of Constrained Optimization
  11. Linear Programming Part I - the Simplex Method
  12. Linear Programming Part II - Interior Point Methods
  13. Quadratic and Convex Programming
  14. Semidefinite and Second-Order Cone Programming
  15. General Nonlinear Optimization Problems
  16. Applications of Constrained Optimization


  1. Basics of Linear Algebra
  2. Basics of Digital Filters

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