# Introduction to Mathematical Programming

Topics in geometric programming are covered in lectures 2-4. (Courtesy of D. Bertsimas and J. N. Tsitsiklis, Introduction to Linear Optimization, Athena Scientific, 1997.)

### Instructor(s)

Prof. Dimitris Bertsimas

### MIT Course Number

6.251J / 15.081J

### As Taught In

Fall 2009

### Level

Graduate

###

Some Description
Instructor(s) | Prof.
As Taught In | Spring 2002
Course Number | 2.24
Level | Undergraduate/Graduate
Features | Lecture Notes, Student Work

## Course Description

## Course Features

- Lecture notes
- Assignments: problem sets (no solutions)

## Course Description

This course is an introduction to linear optimization and its extensions emphasizing the underlying mathematical structures, geometrical ideas, algorithms and solutions of practical problems. The topics covered include: formulations, the geometry of linear optimization, duality theory, the simplex method, sensitivity analysis, robust optimization, large scale optimization network flows, solving problems with an exponential number of constraints and the ellipsoid method, interior point methods, semidefinite optimization, solving real world problems problems with computer software, discrete optimization formulations and algorithms.

## Other Versions

## Other OCW Versions

Archived versions:

- 6.251J Introduction to Mathematical Programming (Fall 2002)

## Related Content

## Course Collections

See related courses in the following collections:

### Find Courses by Topic

- Computer Science > Algorithms and Data Structures
- Applied Mathematics
- Systems Engineering
- Computer Science > Software Design and Engineering
- Discrete Mathematics

Dimitris Bertsimas. 6.251J Introduction to Mathematical Programming. Fall 2009. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: Creative Commons BY-NC-SA.

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