MATLAB API Overview#

This section documents the Gurobi MATLAB interface. For those of you who are notfamiliar with MATLAB, it is an environment for doing numerical computing. Pleasevisit theMATLAB web site formore information. This manual begins with aquick overview of the methods provided by our MATLAB API. It thencontinues with a comprehensive presentation of all of the available methods,their arguments, and their return values.

For information about how to install the Gurobi MATLAB interface, pleaserefer to theGurobi MATLAB API installation guide.

If you are new to the Gurobi Optimizer, we suggest that you start with theGetting Started Knowledge Base article for general information. This alsoincludesTutorials for the different Gurobi APIs. Additionally, ourExample Tour provides concrete examples of howto use the methods described here. We will point to sections or examples of thistour whenever it fits in this overview.

The MATLAB Optimization Toolbox provides its own interface for buildingoptimization models (starting with version 2017b). Gurobi supports thisinterface as well. We’ll discuss this aspect in theproblem-based modeling section; consult also thelinprog,intlinprog,opttoolbox_lp, andopttoolbox_mip1 examples in the Gurobi distributionfor illustrations of how to pass models built using this interface to Gurobi.

A quick note for new users: the convention in math programming is that variablesare non-negative unless specified otherwise. You’ll need to explicitly set lowerbounds if you want variables to be able to take negative values.

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