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Update: April 2021: The JuMPTutorials.jl repository is archived and will not be maintained. The tutorials from this repository have been moved to the JuMP documentation.

JuMPTutorials.jl

This repository contains tutorials on JuMP, a domain-specific modeling language for mathematical optimization embedded in Julia. Tutorials can be viewed in the form of webpages, and interactive Jupyter notebooks. This set of tutorials is made to complement the documentation by providing practical examples of the concepts. For more details, please consult the JuMP documentation.

These tutorials are currently under development as a part of a Google Summer of Code project. The current list of tutorials that are planned can be viewed at the following issue. If there is a tutorial you would like to request, please add a comment to the above issue. Any other suggestions are welcome as well.

There are also some older notebooks available at juliaopt-notebooks repository. Most of these were built using prior versions of JuMP and may not function correctly, but they can assist in implementing some concepts. There are also some code examples available in the main JuMP repo.

Run Notebooks in the Browser

To try out any of the tutorials in the browser without downloading Julia, click on the launch binder button above. Note that this functionality only supports open-source solvers which do not have additional requirements (for e.g. BLAS or MATLAB). This is also very slow and can take several minutes to start as it has to first install Julia and all the dependencies. Thus, you should download and run the notebooks on your PC for the best experience.

Table of Contents

• Introduction
  • An Introduction to Julia
  • Getting Started with JuMP
  • Variables, Constraints and Objective
  • Solvers and Solutions
• Using JuMP
  • Working with Data Files
  • Problem Modification
  • Nonlinear Modelling
• Optimization Concepts
  • Integer Programming
  • Conic Programming
  • Benders Decomposition
• Modelling Examples
  • Sudoku
  • Problems on Graphs
  • Network Flows
  • Finance
  • Power Systems
  • Geometric Problems
  • Experiment Design
  • Rocket Control
  • N-Queens
  • Facility Location
  • Geographic Clustering With Additional Constraint