| 1 | Introduction |
| 2 | Unconstrained Optimization - Optimality Conditions |
| 3 | Gradient Methods |
| 4 | Convergence Analysis of Gradient Methods |
| 5 | Rate of Convergence |
| 6 | Newton and Gauss - Newton Methods |
| 7 | Additional Methods |
| 8 | Optimization Over a Convex Set; Optimality Conditions |
| 9 | Feasible Direction Methods |
| 10 | Alternatives to Gradient Projection |
| 11 | Constrained Optimization; Lagrange Multipliers |
| 12 | Constrained Optimization; Lagrange Multipliers |
| 13 | Inequality Constraints |
| 14 | Introduction to Duality |
| 15 | Interior Point Methods |
| 16 | Penalty Methods |
| 17 | Augmented Lagrangian Methods |
| 18 | Duality Theory |
| 19 | Duality Theorems |
| 20 | Strong Duality |
| 21 | Dual Computational Methods |
| 22 | Additional Dual Methods |
