Useful Links
Systems Science
Optimization Theory
1. Foundations of Optimization
2. Mathematical Foundations
3. Unconstrained Optimization
4. Constrained Optimization Theory
5. Linear Programming
6. Nonlinear Programming
7. Integer and Combinatorial Optimization
8. Dynamic Programming
9. Stochastic Optimization
10. Heuristic and Metaheuristic Methods
11. Multi-Objective Optimization
12. Specialized Optimization Topics
13. Applications and Case Studies
14. Computational Aspects and Software
Constrained Optimization Theory
Constraint Types and Properties
Equality Constraints
Linear Equality Constraints
Nonlinear Equality Constraints
Constraint Manifolds
Inequality Constraints
Linear Inequality Constraints
Nonlinear Inequality Constraints
Active and Inactive Constraints
Feasible Region Geometry
Constraint Boundaries
Interior and Boundary Points
Regular and Singular Points
Optimality Conditions
Lagrange Multiplier Theory
Method of Lagrange Multipliers
Lagrangian Function
Interpretation of Multipliers
Karush-Kuhn-Tucker (KKT) Conditions
Stationarity Condition
Primal Feasibility
Dual Feasibility
Complementary Slackness
First-Order Necessary Conditions
Second-Order Conditions
Bordered Hessian
Sufficient Conditions for Constrained Problems
Constraint Qualifications
Linear Independence Constraint Qualification (LICQ)
Mangasarian-Fromovitz Constraint Qualification (MFCQ)
Constant Rank Constraint Qualification (CRCQ)
Slater's Condition for Convex Problems
Abadie's Constraint Qualification
Duality Theory
Lagrangian Duality
Dual Function
Dual Problem Formulation
Weak Duality Theorem
Strong Duality Theorem
Duality Gap
Saddle Point Conditions
Previous
3. Unconstrained Optimization
Go to top
Next
5. Linear Programming