Course Chapters
Explore our comprehensive curriculum covering linear and nonlinear programming
Table of Contents
Chapter 1: Introduction to Optimization
Basic concepts and terminology in optimization theory
Chapter 2: Basic Properties of Linear Programs
Formulation and solution methods for linear programming problems
Chapter 3: The Simplex Method
The fundamental algorithm for solving linear programming problems
Chapter 4: Duality and Complementarity
Understanding the relationship between primal and dual problems
Chapter 5: Interior-Point Methods
Modern approaches to solving optimization problems
Chapter 6: Conic Linear Programming
Fundamentals and applications of nonlinear optimization
Chapter 7: Basic Properties of Solutions and Algorithms
Methods and techniques for solving constrained optimization problems
Chapter 8: Basic Descent Methods
Techniques for solving optimization problems without constraints
Chapter 9: Conjugate Direction Methods
Modern approaches to solving optimization problems
Chapter 10: Quasi-Newton Methods
Techniques for finding global optima in complex problems
Chapter 11: Constrained Minimization Conditions
Understanding conditions for constrained optimization
Chapter 12: Primal Methods
Methods for solving constrained optimization problems
Chapter 13: Penalty and Barrier Methods
Methods for handling constraints in optimization
Chapter 14: Duality and Dual Methods
Understanding duality in optimization
Chapter 15: Primal-Dual Methods
Combining primal and dual approaches in optimization
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