# SE/EC/ME 724 Advanced Optimization Theory and Methods

### Spring 2018

### Prerequisites

SE/EC 524/674 or consent of instructor.

### Description

Complements SE/EC 524/674 by introducing advanced optimization techniques. Emphasis on nonlinear optimization and recent developments in the field. Topics include: unconstrained optimization methods such as gradient and incremental gradient, conjugate direction, Newton and quasi-Newton methods; constrained optimization methods such as projection, feasible directions, barrier and interior point methods; duality theory and methods; convex duality; and stochastic approximation algorithms. Introduction to modern convex optimization including semi-definite programming, conic programming, and robust optimization. Applications drawn from control, production and capacity planning, resource allocation, communication and sensor networks, and bioinformatics.

### Instructor

Yannis Paschalidis

### Class Meets

Mo, We, 12:20pm-2:05pm at CAS 424.

### Course Information

Pick up a hard copy of a more detailed Course Information Sheet.

### Lecture Notes and Problem sets

- Lecture 1
- Lecture 2
- Lecture 3
- Problem Set 1
- Lecture 4
- Lecture 5
- Lecture 6
- Problem Set 2
- Lecture 7
- Lecture 8
- Lecture 9
- Problem Set 3
- Lecture 10
- Lecture 11
- Problem Set 4
- Term Project Description
- Lecture 12
- Lecture 13
- Problem Set 5
- Lecture 14
- Lecture 15
- Lecture 16
- Lecture 17
- Problem Set 6
- Lecture 18
- Lecture 19
- Lecture 20
- Lecture 21
- Lecture 22
- Lecture 23
- Project Presentations