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