Tutorial: Mixed-Integer Linear Programming

This video tutorial takes you through the foundational principles of Mixed-Integer Linear Programming. You will learn why mixed-integer programming (MIP) is important, methods for solving a MIP problem, the advantages of using MIP instead of heuristics, and more.

 

Mixed-Integer Linear Programming Tutorial Overview

Chapter #1: Why Mixed-Integer Programming (MIP)

Chapter #2: Resource Assignment Problem

Chapter #3: Linear Programming Formulations

Chapter #4: Linear Programming Formulation With Gurobi Python API

Chapter #5: Jupyter Notebook #1 Resource Assignment Problem Formulation

Chapter #6: Perfect Formulation Resource Assignment Problem (RAP)

Chapter #7: Jupyter Notebook #2 Perfect Formulation Resource Assignment Problem

Chapter #8: Methods for Solving MIP Problems

Chapter #9: Approach 1 Branch And Bound Methods For Solving MIP Problems Part 1

Chapter #10: Approach 1 Branch And Bound Methods For Solving MIP Problems Part II

Chapter #11: Approach 2 Cutting Planes Methods For Solving MIP Problems

Chapter #12: Jupyter Notebook #3 - Why MIP Is Better than Simple Heuristics

 


Summary & Conclusion: Mixed Integer Linear Programming

To download the PDF of the Tutorial Slides, please click here.

To download the RAP Problem 001 Jupyter Notebook file please click here.

To download the RAP Problem 002 Jupyter Notebook file please click here.

 

Request a Gurobi Evaluation License or Free Academic License

The RAP Problem is coded using the Gurobi Python API in Jupyter Notebook. In order to use the Jupyter Notebooks, you must have a Gurobi License. If you do not have a license, you can request an Evaluation License as a Commercial User or download a free license as an Academic User.

Commercial Users: Free Evaluation Version Academic Users: Free Academic Version