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Systems Optimization: Models and Computation (SMA 5223)

Art: C. Morrison (engraver); Dodd, Robert (artist and…, An Outward bound East Indiaman sailing from the Downs - RMG PY8445, 29 May 1788 · Public domain

Instructors: Prof. Jie Sun, Prof. Robert Freund, Prof. Thomas Magnanti
Term: Spring 2004
Level: Graduate
What's inside: 1 lecture note · 36 other files · 3 web pages
Materials open: MIT OCW

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Source: MIT OpenCourseWare 15.094J Systems Optimization: Models and Computation (SMA 5223), Spring 2004, Prof. Jie Sun, Prof. Robert Freund, Prof. Thomas Magnanti — original course page on ocw.mit.edu ↗. License: CC BY-NC-SA 4.0. Study order: MIT's own listing order, section by section. Taken from MIT's published course files, downloaded from ocw.mit.edu on September 23, 2026. How RedLectern is built.

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MIT OpenCourseWare, Prof. Jie Sun, Prof. Robert Freund, Prof. Thomas Magnanti, 15.094J Systems Optimization: Models and Computation (SMA 5223), Spring 2004.

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Systems Optimization: Models and Computation (SMA 5223)

Before you start

What's here, and what isn't

Not included here

Materials by section

Lecture Notes

Assignments

Other materials from this course

Lecture 1: Overview of Optimization Models; and Radiation Therapy

Lecture 2: Computer Solution and Issues in Solving Linear Optimization

Lecture 3: Applied Lagrange Duality

Lecture 4: Simple Routines for Optimization

Lecture 5: Telecommunications Systems Design Problem

Lecture 6: Column Generation, I

Lecture 7: Column Generation, II

Lecture 8: Discrete Optimization, I

Lecture 9: Convex Constrained Optimization Models

Lecture 10: Discrete Optimization, II

Lecture 11: Discrete Optimization, III

Lecture 12: Pattern Classification: Separable Problems

Lecture 13: Pattern Classification and QP Methods, I

Lecture 14: QP and Nonlinear Methods, II

Lecture 15: E-commerce Application

Lecture 16: Truss Design and SOCP, I

Lecture 17: Truss Design and SOCP, II

Lecture 18: Issues in Non-Convex Optimization

Lecture 19: Stochastic Linear Optimization, and Extensions

Lecture 20: Stochastic LP and Benders Decomposition

Lecture 21: Semi-Definite Optimization, I

Lecture 22: Semi-Definite Optimization, II

Lecture 23: Traffic Control Models, I

Lecture 24: Traffic Control Models, II