Gurobi
Handling Gurobi licenses through the APPSI interface
In order to obtain performance benefits when re-solving a Pyomo model
with Gurobi repeatedly, Pyomo has to keep a reference to a gurobipy
model between calls to
solve()
. Depending
on the Gurobi license type, this may “consume” a license as long as
any APPSI-Gurobi interface exists (i.e., has not been garbage
collected). To release a Gurobi license for other processes, use the
release_license()
method as shown below. Note that
release_license()
must be called on every instance for this to actually release the
license. However, releasing the license will delete the gurobipy model
which will have to be reconstructed from scratch the next time
solve()
is
called, negating any performance benefit of the persistent solver
interface.
>>> opt = appsi.solvers.Gurobi()
>>> results = opt.solve(model)
>>> opt.release_license()
Also note that both the
available()
and
solve()
methods
will construct a gurobipy model, thereby (depending on the type of
license) “consuming” a license. The
available()
method has to do this so that the availability does not change between
calls to
available()
and
solve()
, leading
to unexpected errors.
- class pyomo.contrib.appsi.solvers.gurobi.Gurobi(only_child_vars=False)[source]
Bases:
PersistentBase
,PersistentSolver
Interface to Gurobi
- enum Availability(value)
Bases:
IntEnum
An enumeration.
- Member Type:
Valid values are as follows:
- NotFound = <Availability.NotFound: 0>
- BadVersion = <Availability.BadVersion: -1>
- BadLicense = <Availability.BadLicense: -2>
- FullLicense = <Availability.FullLicense: 1>
- LimitedLicense = <Availability.LimitedLicense: 2>
- NeedsCompiledExtension = <Availability.NeedsCompiledExtension: -3>
- add_block(block)
- available()[source]
Test if the solver is available on this system.
Nominally, this will return True if the solver interface is valid and can be used to solve problems and False if it cannot.
Note that for licensed solvers there are a number of “levels” of available: depending on the license, the solver may be available with limitations on problem size or runtime (e.g., ‘demo’ vs. ‘community’ vs. ‘full’). In these cases, the solver may return a subclass of enum.IntEnum, with members that resolve to True if the solver is available (possibly with limitations). The Enum may also have multiple members that all resolve to False indicating the reason why the interface is not available (not found, bad license, unsupported version, etc).
- Returns:
available – An enum that indicates “how available” the solver is. Note that the enum can be cast to bool, which will be True if the solver is runable at all and False otherwise.
- Return type:
- cbCut(con)[source]
Add a cut within a callback.
- Parameters:
con (pyomo.core.base.constraint.ConstraintData) – The cut to add
- cbLazy(con)[source]
- Parameters:
con (pyomo.core.base.constraint.ConstraintData) – The lazy constraint to add
- property config: GurobiConfig
An object for configuring solve options.
- Returns:
An object for configuring pyomo solve options such as the time limit. These options are mostly independent of the solver.
- Return type:
- get_linear_constraint_attr(con, attr)[source]
Get the value of an attribute on a gurobi linear constraint.
- Parameters:
con (pyomo.core.base.constraint.ConstraintData) – The pyomo constraint for which the corresponding gurobi constraint attribute should be retrieved.
attr (str) – The attribute to get. See the Gurobi documentation
- get_model_attr(attr)[source]
Get the value of an attribute on the Gurobi model.
- Parameters:
attr (str) – The attribute to get. See Gurobi documentation for descriptions of the attributes.
- get_quadratic_constraint_attr(con, attr)[source]
Get the value of an attribute on a gurobi quadratic constraint.
- Parameters:
con (pyomo.core.base.constraint.ConstraintData) – The pyomo constraint for which the corresponding gurobi constraint attribute should be retrieved.
attr (str) – The attribute to get. See the Gurobi documentation
- get_reduced_costs(vars_to_load=None)[source]
- Parameters:
vars_to_load (list) – A list of the variables whose reduced cost should be loaded. If vars_to_load is None, then all reduced costs will be loaded.
- Returns:
reduced_costs – Maps variable to reduced cost
- Return type:
ComponentMap
- get_sos_attr(con, attr)[source]
Get the value of an attribute on a gurobi sos constraint.
- Parameters:
con (pyomo.core.base.sos.SOSConstraintData) – The pyomo SOS constraint for which the corresponding gurobi SOS constraint attribute should be retrieved.
attr (str) – The attribute to get. See the Gurobi documentation
- get_var_attr(var, attr)[source]
Get the value of an attribute on a gurobi var.
- Parameters:
var (pyomo.core.base.var.VarData) – The pyomo var for which the corresponding gurobi var attribute should be retrieved.
attr (str) – The attribute to get. See gurobi documentation
- property gurobi_options
A dictionary mapping solver options to values for those options. These are solver specific.
- Returns:
A dictionary mapping solver options to values for those options
- Return type:
- is_persistent()
- Returns:
is_persistent – True if the solver is a persistent solver.
- Return type:
- load_vars(vars_to_load=None, solution_number=0)[source]
Load the solution of the primal variables into the value attribute of the variables.
- Parameters:
vars_to_load (list) – A list of the variables whose solution should be loaded. If vars_to_load is None, then the solution to all primal variables will be loaded.
- remove_block(block)
- set_callback(func=None)[source]
Specify a callback for gurobi to use.
- Parameters:
func (function) –
The function to call. The function should have three arguments. The first will be the pyomo model being solved. The second will be the GurobiPersistent instance. The third will be an enum member of gurobipy.GRB.Callback. This will indicate where in the branch and bound algorithm gurobi is at. For example, suppose we want to solve
\[ \begin{align}\begin{aligned}min 2*x + y\\s.t.\\ y >= (x-2)**2\\ 0 <= x <= 4\\ y >= 0\\ y integer\end{aligned}\end{align} \]as an MILP using extended cutting planes in callbacks.
>>> from gurobipy import GRB >>> import pyomo.environ as pe >>> from pyomo.core.expr.taylor_series import taylor_series_expansion >>> from pyomo.contrib import appsi >>> >>> m = pe.ConcreteModel() >>> m.x = pe.Var(bounds=(0, 4)) >>> m.y = pe.Var(within=pe.Integers, bounds=(0, None)) >>> m.obj = pe.Objective(expr=2*m.x + m.y) >>> m.cons = pe.ConstraintList() # for the cutting planes >>> >>> def _add_cut(xval): ... # a function to generate the cut ... m.x.value = xval ... return m.cons.add(m.y >= taylor_series_expansion((m.x - 2)**2)) ... >>> _c = _add_cut(0) # start with 2 cuts at the bounds of x >>> _c = _add_cut(4) # this is an arbitrary choice >>> >>> opt = appsi.solvers.Gurobi() >>> opt.config.stream_solver = True >>> opt.set_instance(m) >>> opt.gurobi_options['PreCrush'] = 1 >>> opt.gurobi_options['LazyConstraints'] = 1 >>> >>> def my_callback(cb_m, cb_opt, cb_where): ... if cb_where == GRB.Callback.MIPSOL: ... cb_opt.cbGetSolution(vars=[m.x, m.y]) ... if m.y.value < (m.x.value - 2)**2 - 1e-6: ... cb_opt.cbLazy(_add_cut(m.x.value)) ... >>> opt.set_callback(my_callback) >>> res = opt.solve(m)
- set_gurobi_param(param, val)[source]
Set a gurobi parameter.
- Parameters:
param (str) – The gurobi parameter to set. Options include any gurobi parameter. Please see the Gurobi documentation for options.
val (any) – The value to set the parameter to. See Gurobi documentation for possible values.
- set_linear_constraint_attr(con, attr, val)[source]
Set the value of an attribute on a gurobi linear constraint.
- Parameters:
con (pyomo.core.base.constraint.ConstraintData) – The pyomo constraint for which the corresponding gurobi constraint attribute should be modified.
attr (str) –
- The attribute to be modified. Options are:
CBasis DStart Lazy
val (any) – See gurobi documentation for acceptable values.
- set_objective(obj: ObjectiveData)
- set_var_attr(var, attr, val)[source]
Set the value of an attribute on a gurobi variable.
- Parameters:
var (pyomo.core.base.var.VarData) – The pyomo var for which the corresponding gurobi var attribute should be modified.
attr (str) –
- The attribute to be modified. Options are:
Start VarHintVal VarHintPri BranchPriority VBasis PStart
val (any) – See gurobi documentation for acceptable values.
- solve(model, timer: HierarchicalTimer | None = None) Results [source]
Solve a Pyomo model.
- Parameters:
model (BlockData) – The Pyomo model to be solved
timer (HierarchicalTimer) – An option timer for reporting timing
- Returns:
results – A results object
- Return type:
- property symbol_map
- update(timer: HierarchicalTimer | None = None)[source]
- property update_config