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. A few fields are mandatory: the constraint matrix (A),
the objective vector (obj), the right-hand side vector
(rhs), and the constraint sense vector (sense). A model
can also include optional fields (e.g., the objective
sense modelsense).
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.
Subsequent statements populate other fields of the model
variable, including the objective vector, the right-hand-side vector,
and the constraint sense vector.
In addition to the mandatory fields, this example also sets two
optional 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 fields 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.
