Last week I had the pleasure of being invited to the Second annual JuMP-dev workshop, which happened in June 27-29, 2018 at Bordeaux, France. I’ve presented the packages from the Julia Smooth Optimizers organization, and had a very good time meeting with the JuMP developers.
For those still unaware, JuMP is a modelling language for Mathematical Programming written in Julia. It provides access to a few different solvers for many kinds of problems, and it works inside of Julia, so one can enjoy the advantages of having a robust language if there is a need for advanced usage.
I’ve used Julia in classes since 2016 for teaching numerical calculus, and the packages of Julia Smooth Optimizers for nonlinear optimization this last semester. I’ve taught a quick tutorial on JuMP in that class to solve a few nonlinear problems, and discuss the starting point dependency of nonlinear solvers. The notebook can be found here in portuguese.