# Syllabus

## Course Meeting Times

Lectures: 2 sessions / week, 1.5 hours / session

## Description

This class is a computational and application-oriented introduction to the modeling of large-scale systems in a wide variety of decision-making domains and the optimization of such systems using state-of-the-art optimization software. Application domains include transportation and logistics, pattern classification, structural design, financial engineering, and telecommunications system planning. Modeling tools and techniques covered include linear, network, discrete, and nonlinear optimization, heuristic methods, sensitivity and post-optimality analysis, decomposition methods for large-scale systems, and stochastic optimization. This course is oriented around computation and computation-related issues in developing and solving large-scale optimization models.

## Prerequisites

MIT subject 15.093J or 15.081J / 6.251J, or permission of instructor

## Course Texts

Bertsimas, D., and J. Tsitsiklis. Introduction to Linear Optimization. Belmont, MA: Athena Scientific, 1997. ISBN: 1886529191.

Van Hentenryck, Pascal. The OPL Optimization Programming Language. Cambridge, MA: MIT Press, 1999. ISBN: 0262720302.

## Grading Assessment

Assessment Table
Activities | percentages
--- | ---
Problem Sets | 35%
Midterm Exam | 30%
Final Project | 25%
Class Interaction | 10%