Python III Webinar

Optimization and Heuristics

The Gurobi Python interface combines the ease and expressiveness of a modeling language with the power and flexibility of a programming language. This part three of a three-part series builds on the ideas presented in our Python I and Python II webinars.

In this webinar, you will:

  • To use the Gurobi MIP solver as a heuristic for quickly obtaining good quality feasible solutions
  • About MIP's ability to not only find initial feasible solutions, but also to improve on these solutions, often turning poor quality solutions into excellent solutions very quickly
  • About using MIP as a framework for structuring a heuristic search of a large space of possible solutions
  • Advanced techniques such as MIP starts, variable hints, and heuristic callbacks. These techniques will be illustrated with Python examples

You can download the Jupyter notebook and examples associated with this webinar here.

Getting Gurobi

Whether you are new to optimization or switching from a competing solver, we've worked hard to make getting started with Gurobi easier for you.

Using Gurobi

To help you be as productive as possible, we offer a detailed reference manual along with numerous code examples and a wide range of videos.


At Gurobi, we provide our customers direct access to PhD-level optimization experts with years of experience working with commercial models.