Building the model
The example begins by building an optimization model. The data
associated with an optimization model must be stored in a MATLAB
struct. Fields in this struct contain the different parts of
the model. The most fundamental fields are: The constraint matrix
(A), the objective vector (obj), the right-hand side
vector (rhs), and the constraint sense vector (sense).
Among these, only the constraint matrix is mandatory, and default
values are substituted for all other model fields in case they are
missing.
The example uses the built-in sparse function to build the
constraint matrix A. The Gurobi MATLAB interface only accepts
sparse matrices as input. If you have a dense matrix, use
sparse to convert it to a sparse matrix before passing it to
our interface.
In addition to the fields discussed above, this example sets two
more fields: modelsense and vtype. The former is
used to indicate the sense of the objective function. The default is
minimization, so we've set the field equal to 'max' to
indicate that we would like to maximize the specified objective. The
vtype field is used to indicate the types of the variables in
the model. In our example, all variables are binary ('B').
Note that our interface allows you to specify a scalar value for the
sense and vtype arguments. The Gurobi interface will
expand that scalar to a constant array of the appropriate length. In
this example, the scalar value 'B' will be expanded to an
array of length 3, containing one 'B' value for each column of
A.
