Course Meeting Times
Lectures: 2 sessions / week, 1.5 hours / session
Recitations: 1 session / week, 1 hour / session
Course Content
The course takes a unified view of optimization and covers the main areas of application and the main optimization algorithms. It covers the following topics:
- Linear optimization
- Robust optimization
- Network flows
- Discrete optimization
- Dynamic optimization
- Nonlinear optimization
Tools
ILOG AMPL CPLEX User Guide (PDF)
Contains useful AMPL/CPLEX directives
AMPL Tutorial (PDF)
Course Requirements and Grading
Grades will be determined by performance on the following requirements. Weights are approximate, and class participation is an important tie breaker.
| ACTIVITIES | PERCENTAGES |
|---|---|
| Homework | 30% |
| Midterm exam | 30% |
| Final exam | 40% |
Calendar
| LEC # | TOPICS |
|---|---|
| 1 | Applications of linear optimization |
| 2 | Geometry of linear optimization |
| 3-4 | Simplex method |
| 5-6 | Duality theory |
| 7 | Sensitivity analysis |
| 8 | Robust optimization |
| 9 | Large scale optimization |
| 10-11 | Network flows |
| 12 | Applications of discrete optimization |
| 13 | Branch and bound and cutting planes |
| Midterm exam | |
| 14 | Lagrangean methods |
| 15 | Heuristics and approximation algorithms |
| 16 | Dynamic programming |
| 17 | Applications of nonlinear optimization |
| 18 | Optimality conditions and gradient methods |
| 19 | Line searches and Newton’s method |
| 20 | Conjugate gradient methods |
| 21 | Affine scaling algorithm |
| 22 | Interior point methods |
| 23-24 | Semidefinite optimization I |
| Final exam |
