Gurobi

(class from pyomo.contrib.appsi.solvers.gurobi)

class pyomo.contrib.appsi.solvers.gurobi.Gurobi(only_child_vars=False)[source]

Bases: PersistentBase, PersistentSolver

Interface to Gurobi

__init__(only_child_vars=False)[source]

Methods

`__init__`([only_child_vars])
`add_block`(block)
`add_constraints`(cons)
`add_params`(params)
`add_sos_constraints`(cons)
`add_variables`(variables)
`api_version`()	Return the public API supported by this interface.
`available`()	Test if the solver is available on this system.
`cbCut`(con)	Add a cut within a callback.
`cbGet`(what)
`cbGetNodeRel`(vars)
`cbGetSolution`(vars)
`cbLazy`(con)
`cbSetSolution`(vars, solution)
`cbUseSolution`()
`get_duals`([cons_to_load])	Declare sign convention in docstring here.
`get_gurobi_param_info`(param)	Get information about a gurobi parameter.
`get_linear_constraint_attr`(con, attr)	Get the value of an attribute on a gurobi linear constraint.
`get_model_attr`(attr)	Get the value of an attribute on the Gurobi model.
`get_primals`([vars_to_load, solution_number])
`get_quadratic_constraint_attr`(con, attr)	Get the value of an attribute on a gurobi quadratic constraint.
`get_reduced_costs`([vars_to_load])
`get_slacks`([cons_to_load])
`get_sos_attr`(con, attr)	Get the value of an attribute on a gurobi sos constraint.
`get_var_attr`(var, attr)	Get the value of an attribute on a gurobi var.
`is_persistent`()
`load_vars`([vars_to_load, solution_number])	Load the solution of the primal variables into the value attribute of the variables.
`release_license`()
`remove_block`(block)
`remove_constraints`(cons)
`remove_params`(params)
`remove_sos_constraints`(cons)
`remove_variables`(variables)
`reset`()
`set_callback`([func])	Specify a callback for gurobi to use.
`set_gurobi_param`(param, val)	Set a gurobi parameter.
`set_instance`(model)
`set_linear_constraint_attr`(con, attr, val)	Set the value of an attribute on a gurobi linear constraint.
`set_objective`(obj)
`set_var_attr`(var, attr, val)	Set the value of an attribute on a gurobi variable.
`solve`(model[, timer])	Solve a Pyomo model.
`update`([timer])
`update_params`()
`update_variables`(variables)
`version`()
`write`(filename)	Write the model to a file (e.g., and lp file).

Attributes

`config`	An object for configuring solve options.
`gurobi_options`	A dictionary mapping solver options to values for those options.
`symbol_map`
`update_config`

Member Documentation

enum Availability(value)

Bases: IntEnum

as_integer_ratio()

Return a pair of integers, whose ratio is equal to the original int.

The ratio is in lowest terms and has a positive denominator.

>>> (10).as_integer_ratio()
(10, 1)
>>> (-10).as_integer_ratio()
(-10, 1)
>>> (0).as_integer_ratio()
(0, 1)

bit_count()

Number of ones in the binary representation of the absolute value of self.

Also known as the population count.

>>> bin(13)
'0b1101'
>>> (13).bit_count()
3

bit_length()

Number of bits necessary to represent self in binary.

>>> bin(37)
'0b100101'
>>> (37).bit_length()
6

conjugate(): Returns self, the complex conjugate of any int.

classmethod from_bytes(bytes, byteorder='big', *, signed=False)

Return the integer represented by the given array of bytes.

bytes: Holds the array of bytes to convert. The argument must either support the buffer protocol or be an iterable object producing bytes. Bytes and bytearray are examples of built-in objects that support the buffer protocol.
byteorder: The byte order used to represent the integer. If byteorder is ‘big’, the most significant byte is at the beginning of the byte array. If byteorder is ‘little’, the most significant byte is at the end of the byte array. To request the native byte order of the host system, use sys.byteorder as the byte order value. Default is to use ‘big’.
signed: Indicates whether two’s complement is used to represent the integer.

is_integer(): Returns True. Exists for duck type compatibility with float.is_integer.

to_bytes(length=1, byteorder='big', *, signed=False)

Return an array of bytes representing an integer.

length: Length of bytes object to use. An OverflowError is raised if the integer is not representable with the given number of bytes. Default is length 1.
byteorder: The byte order used to represent the integer. If byteorder is ‘big’, the most significant byte is at the beginning of the byte array. If byteorder is ‘little’, the most significant byte is at the end of the byte array. To request the native byte order of the host system, use sys.byteorder as the byte order value. Default is to use ‘big’.
signed: Determines whether two’s complement is used to represent the integer. If signed is False and a negative integer is given, an OverflowError is raised.

denominator: the denominator of a rational number in lowest terms

imag: the imaginary part of a complex number

numerator: the numerator of a rational number in lowest terms

real: the real part of a complex number

classmethod api_version()

Return the public API supported by this interface.

Returns:: A solver API enum object
Return type:: SolverAPIVersion

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 runnable at all and False otherwise.
Return type:: Solver.Availability

cbCut(con)[source]

Add a cut within a callback.

Parameters:: con (pyomo.core.base.constraint.ConstraintData) – The cut to add

cbGetNodeRel(vars)[source]

Parameters:: vars (Var or iterable of Var)

cbGetSolution(vars)[source]

Parameters:: vars (iterable of vars)

cbLazy(con)[source]

Parameters:: con (pyomo.core.base.constraint.ConstraintData) – The lazy constraint to add

get_duals(cons_to_load=None)[source]

Declare sign convention in docstring here.

Parameters:: cons_to_load (list) – A list of the constraints whose duals should be loaded. If cons_to_load is None, then the duals for all constraints will be loaded.
Returns:: duals – Maps constraints to dual values
Return type:: dict

get_gurobi_param_info(param)[source]

Get information about a gurobi parameter.

Parameters:: param (str) – The gurobi parameter to get info for. See Gurobi documentation for possible options.
Return type:: six-tuple containing the parameter name, type, value, minimum value, maximum value, and default value.

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_slacks(cons_to_load=None)[source]

Parameters:: cons_to_load (list) – A list of the constraints whose slacks should be loaded. If cons_to_load is None, then the slacks for all constraints will be loaded.
Returns:: slacks – Maps constraints to slack values
Return type:: dict

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

is_persistent()

Returns:: is_persistent – True if the solver is a persistent solver.
Return type:: bool

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.

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 pyo
>>> from pyomo.core.expr.taylor_series import taylor_series_expansion
>>> from pyomo.contrib import appsi
>>>
>>> m = pyo.ConcreteModel()
>>> m.x = pyo.Var(bounds=(0, 4))
>>> m.y = pyo.Var(within=pyo.Integers, bounds=(0, None))
>>> m.obj = pyo.Objective(expr=2*m.x + m.y)
>>> m.cons = pyo.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_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) → 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:

Results

version()[source]

Returns:: version – A tuple representing the version
Return type:: tuple

write(filename)[source]

Write the model to a file (e.g., and lp file).

Parameters:: filename (str) – Name of the file to which the model should be written.

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:: SolverConfig

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:: dict