10h30 - 12h00
Algebraic modeling for optimization with JuMP
This hands-on tutorial will introduce participants to JuMP, an algebraic modeling language like AMPL and GAMS which enables users to solve linear, mixed integer, quadratic, and nonlinear optimization problems by expressing them in a natural, algebraic form. Less than three years since its initial release, JuMP has been used for teaching at over 10 universities, in research projects in energy, transportation, and statistical inference, and in industry. JuMP is embedded in Julia, a high-level, fast, open-source programming language targeted at scientific computing. We do not assume prior experience with Julia, although we will not cover its syntax in detail. The tutorial will be structured using Jupyter notebooks.