Syllabus

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:

  1. Linear optimization
  2. Robust optimization
  3. Network flows
  4. Discrete optimization
  5. Dynamic optimization
  6. Nonlinear optimization

Tools

AMPL Student Version Download

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

Course Info

Learning Resource Types

assignment Problem Sets
grading Exams
notes Lecture Notes