6.252J | Spring 2003 | Graduate

Nonlinear Programming

Lecture Notes

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