This year’s Advent of Code is well past the half-way mark, and I’ve been reflecting on some of the harder or more interesting problems over the last few years, and the lessons learned about making code faster, or large problems tractable. In case you haven’t encountered it, AoC is an annual coding competition, with a new problem every day, from December 1 through 25. Each day, there are two parts, and the second (usually harder) part unlocks after you solve the first part.

I’ve been away helping Bain set up a new capability in generative AI, on the back of our OpenAI partnership, and am coming back to standard data science problems. In this post, I’d like to share some experiments doing linear programming optimization, using Gonum’s optimization library. It’s a very basic facility, but has helped me learn how to set up problems using the venerable Simplex algorithm, first developed by George Danzig in 1947.

If you are new to Go, here is the basic process for setting up a new project and building/running it. This assumes that you have already installed Go as described in the previous blog post. First, create a working directory for the project, and change into it: mkdir ~/myproject cd ~/myproject Then, use your favorite text editor or IDE to create a Go program, with any name that ends in .