Modern Convex Optimization
Course Description:
Theory and algorithms for constrained convex optimization including optimality conditions, duality theory, applications, interior-point methods, penalty and barrier methods.
Textbooks:
- Convex Optimization, by Stephen Boyd and Lieven Vandenberghe. Cambridge University Press. ISBN: 9780521833783
- Combinatorial and Algorithmic Mathematics: From Foundation to Optimization, by Baha Alzalg. John Wiley & Sons. ISBN: 9781394235940.
Topic Outline and Schedule:
The following is a rough plan. As the course progresses, I may include
new topics and/or delete some of the ones listed here.
Topics
|
Weeks
|
1. Convexity, Polyhedra and Cones, Farkas’ Lemma
|
1
|
2. Analysis of Algorithms
|
2, 3
|
3. Matrix/Array and Numeric Algorithms
|
4
|
4. Linear Programming
|
5-7
|
5. General Convex Programming
|
8-10
|
6. Second-Order Cone Programming
|
11-13
|
7. Semidefinte Programming
|
14-16
|