Modeling With the Gurobi Python API
This 50 minute tutorial illustrates the modeling features of the Gurobi Python API.
Gurobi Python Interface: Matrix-friendly Modeling Techniques
Watch this 30-minute video to learn about a new set of API functions within the Gurobi Python interface (“gurobipy”) that support matrix-oriented modeling.
Tech Talk & Chat– Converting Weak to Strong MIP Formulations, Part II
Watch Part 2 of this Tech Talk on converting weak to strong MIP formulations.
Tech Talk & Chat– Converting Weak to Strong MIP Formulations
Watch this Tech Talk on converting weak to strong MIP formulations. Key members of the Gurobi team will distinguish weak formulations from strong ones, from the perspective of the models and associated physical systems rather than the underlying theory.
Switching to Gurobi From Another Solver
We often get questions asking how easy it is to switch to Gurobi and what help is available if it is needed. The general answer is that switching to Gurobi is much easier than many people think. The majority of switchers are able to migrate their model(s) on their own using resources already available on www.gurobi.com.
Products of Variables in Mixed Integer Programming
Products of problem variables appear naturally in quadratic programs. Special preprocessing, linearization and cutting plane techniques are available to deal with such products. If at least one of the two variables in a product is binary, then the product can be modeled using a set of linear constraints. As a consequence, there are many mixed integer linear programs (MILPs) that actually contain products of variables hidden in their constraint structure. Rediscovering these product relationships between the variables enables us to exploit the solving techniques for product terms.
Non-Convex Quadratic Optimization
This video shows one of the major new feature in Gurobi 9.0, the new bilinear solver, which allows users to solve problems with non-convex quadratic objectives and constraints such as QPs, QCPs, MIQPs, and MIQCPs.
Learn How to Design and Deploy Optimization Applications
In this webinar, we showcase the power of mathematical optimization applications and demonstrate how you can deploy these applications on modern IT architectures.
Interactive Shell Overview Video
This 75 minute video demonstrates the capabilities of the Gurobi Interactive Shell.
Gurobi QCP and SOCP Optimizer Overview
This 50 minute video covers our new QCP and SOCP optimizer for solving quadratically-constrainted models with Gurobi. This new capability is built on top of an efficient Second-Order Cone Programming (SOCP) solver. This seminar will discuss the design choices we made in building this new optimizer, and the impact of these choices on overall performance and robustness.
