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Load and solve a model from a file
Examples: callback, feasopt, fixanddive, lp, lpmethod, lpmod, mip2, params, sensitivity
One of the most basic tasks you can perform with the Gurobi libraries
is to read a model from a file, optimize it, and report the result.
The lp
(lp_c.c,
lp_c++.cpp,
lp_cs.cs,
Lp.java,
lp.py,
lp_vb.vb) and mip2
(mip2_c.c,
mip2_c++.cpp,
mip2_cs.cs,
Mip2.java,
mip2.m,
mip2.py,
mip2.R,
mip2_vb.vb) examples are
simple illustratations of how this is done in the various supported
Gurobi languages. While the specifics vary from one language to
another, the basic structure remains the same for all languages.
After initializing the Gurobi environment, the examples begin by reading the
model from the specified file. In C, you call the GRBreadmodel()
function:
error = GRBreadmodel(masterenv, argv[1], &model);In C++, this is done by constructing a
GRBModel
object:
GRBModel model = GRBModel(env, argv[1]);In C# and Java, this is also done by constructing a
GRBModel
object:
GRBModel model = new GRBModel(env, args[0]);In Python, this is done via the
read
global function:
model = read(sys.argv[1])
The next step is to invoke the Gurobi optimizer on the model.
In C, you call GRBoptimize()
on the model
variable:
error = GRBoptimize(model);In C++, Java, and Python, this is accomplished by calling the
optimize
method on the model
object:
model.optimize();In C#, the first letter of the method name is capitalized:
model.Optimize();A successful
optimize
call populates a set of solution
attributes in the model. For example, once the call completes, the
X
variable attribute contains the solution value for each
variable. Similarly, for continuous models, the Pi
constraint
attribute contains the dual value for each constraint.
The examples then retrieve the value of the model Status
attribute to determine the result of the optimization. In the
lp
example, an optimal solution is written to a solution file
(model.sol
).
There are many other things you can do once you have read and solved
the model. For example, lp
checks the solution status --
which is highly recommended. If the model is found to be infeasible,
this example computes an Irreducible Inconsistent Subsystem (IIS) to
isolate the source of the infeasibility.