> For the complete documentation index, see [llms.txt](https://syl1.gitbook.io/julia-language-a-concise-tutorial/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://syl1.gitbook.io/julia-language-a-concise-tutorial/useful-packages/13-jump.md).

# JuMP

[`JuMP`](https://github.com/JuliaOpt/JuMP.jl) is an algebraic modelling language for mathematical optimisation problems, similar to GAMS, AMPL or Pyomo.

It is solver-independent. It supports also non-linear solvers, providing them with the Gradient and the Hessian.

[This notebook](http://nbviewer.jupyter.org/github/sylvaticus/juliatutorial/blob/master/assets/JuMP.ipynb) provides a commented implementation in JuMP of the classical transport problem found in the GAMS tutorial:

Note: The notebook has been updated to the latest JuMP 0.20

*While an updated, expanded and revised version of this chapter is available in "Chapter 10 - Mathematical Libraries" of* [*Antonello Lobianco (2019), "Julia Quick Syntax Reference", Apress*](https://julia-book.com)*, this tutorial remains in active development.*