This site contains materials for my guest lecture at MIT 18.337/6.338, Modern Numerical Computing in Fall 2018.

You should use the latest version of Julia v1.0. Binaries of Julia for all platforms are available here.

You can download the materials by running

git clone https://github.com/juan-pablo-vielma/18.337-6.338-2018

or downloading this zip file.

Finally, you can install Jupyter and its Julia backend IJulia by running the following code in the Julia REPL.

import Pkg
Pkg.add("IJulia")

Each notebook includes a cell with the commands

import Pkg
Pkg.activate(@__DIR__)
Pkg.instantiate()

that will install all required packages described by the Project.toml and Manifest.toml files in the corresponding folder.

The polynomial optimization example requires having Gurobi and a Mosek license already installed. You can download Gurobi from its download page and you can get an academic license for it by registering with your MIT email here. You can get an academic license for Mosek using this form.

The polynomial optimal control example was developed by Joey Huchette for the 2017 SIAM Conference on Optimization. For more details on this problem you can find Joey's SIAM Opt slides here.