15.093J | Fall 2009 | Graduate

Optimization Methods

Course Description

This course introduces the principal algorithms for linear, network, discrete, nonlinear, dynamic optimization and optimal control. Emphasis is on methodology and the underlying mathematical structures. Topics include the simplex method, network flow methods, branch and bound and cutting plane methods for discrete …
This course introduces the principal algorithms for linear, network, discrete, nonlinear, dynamic optimization and optimal control. Emphasis is on methodology and the underlying mathematical structures. Topics include the simplex method, network flow methods, branch and bound and cutting plane methods for discrete optimization, optimality conditions for nonlinear optimization, interior point methods for convex optimization, Newton’s method, heuristic methods, and dynamic programming and optimal control methods.
Learning Resource Types
Problem Sets
Exams
Lecture Notes
Diagram of nodes and paths in a network.
This course covers various techniques and algorithms for network optimization. (Image by Prof. Dimitris Bertsimas.)