Thanks! I’m glad you enjoyed it. You may also get a kick out of the YouTube hyperlinks in the GitHub readme, especially the advanced methods for establishing convexity one :)
29 karma · joined October 13, 2025
https://github.com/klamike
It's by no means polished, but it can be pretty fun to play around with, visualizing how the iterates of different LP algorithms (described in sections 11, 12 of the book) react to changes in the feasible region/objective, by just dragging the vertices/constraints around.
If you go to https://lpviz.net/?demo it will draw a polytope for you, and click around the interface to show off some of the features. I'm constantly chipping away at it in my free time, I welcome any feedback and suggestions!
lpviz is like Desmos, but for linear programming - I've implemented a few LP solvers in Typescript and hooked them up to a canvas so you can draw a feasible region, set an objective direction, and see how the algorithms work. And it all runs locally, in the browser!
If you go to https://lpviz.net/?demo it should show you a short tour of the features/how to use it.
It's by no means complete but I figured there may be some fellow optimization enthusiasts here who might be interested to take a look :) Super open to feedback, feature requests, comments!
For a 2-min intro to LP, I recommend https://www.youtube.com/watch?v=7ZjmPATPVzI