While we support all major programming languages, most of our users choose our Python API for their modeling and development efforts. Even if you are currently familiar with another programming language, we have witnessed several new users being more productive using our Python API. You can learn more on our Gurobi Python Modeling and Development Environment page.
This Knowledge Base covers software installation, how to obtain and install a license, and an introduction to the Getting Started with the Gurobi API Tutorials.
The Modeling Basics page offers an overview of modeling from creating the conceptual model, to implementing, and finally solving it. The LP Basics and MIP Basics pages are a primer into each problem type as well as overviews of the algorithms used to solve each.
This guide gives an overview of the set of tasks you will likely want to perform with the Gurobi Optimizer, such as loading and solving a model, building and modifying a model, changing parameters, etc. It also contains a set of example code across a range of languages and all source code. You can view the Online Guide.
This manual contains documentation for the C, C++, C#, Java®, Microsoft® .NET, Python, MATLAB, and R interfaces, including sections on Attributes and Parameters. You can access the Reference Manual here.
Learn how to use the Gurobi Cloud – a remote Gurobi service via cloud computing. The Gurobi Cloud allows you to run one or more Gurobi Compute Servers without having to purchase new computers or new Gurobi licenses. You can also use cloud instances as workers for distributed optimization. Before using the Gurobi Cloud, please familiarize yourself with Gurobi Remote Services.
In this moderated Gurobi Community Discussion Forum, users can read and post questions about the Gurobi Optimizer. You can also read current and past messages and knowledge base articles.
Choose the evaluation license that fits you best, and start working with our Expert Team for technical guidance and support.
Request free trial hours, so you can see how quickly and easily a model can be solved on the cloud.