def solve(self, sense=None):
"""Solve problem."""
if sense is not None:
self.set_objective_sense(sense)
parm = swiglpk.glp_smcp()
swiglpk.glp_init_smcp(parm)
if self._do_presolve:
parm.presolve = swiglpk.GLP_ON
self._do_presolve = False
else:
parm.presolve = swiglpk.GLP_OFF
logger.debug('Solving using glp_simplex()')
r = swiglpk.glp_simplex(self._p, parm)
if r in (swiglpk.GLP_ENOPFS, swiglpk.GLP_ENODFS):
self._result = Result(self, r)
return self._result
elif r != 0:
raise GLPKError('glp_simplex: {}'.format(r))
if swiglpk.glp_get_num_int(self._p) == 0:
self._result = Result(self)
else:
# The intopt MILP solver need an optimal solution to the LP
# relaxation. Therefore, glp_simplex has to run before glp_intopt
# for MILP problems.
logger.debug('Solving using glp_intopt()')
r = swiglpk.glp_intopt(self._p, None)
if r != 0:
raise GLPKError('glp_intopt: {}'.format(r))
self._result = MIPResult(self)
return self._result
def solve(self, sense=None):
"""Solve problem."""
if sense is not None:
self.set_objective_sense(sense)
parm = swiglpk.glp_smcp()
swiglpk.glp_init_smcp(parm)
parm.presolve = swiglpk.GLP_ON
logger.debug('Solving using glp_simplex()')
r = swiglpk.glp_simplex(self._p, parm)
if r in (swiglpk.GLP_ENOPFS, swiglpk.GLP_ENODFS):
self._result = Result(self, r)
return self._result
elif r != 0:
raise GLPKError('glp_simplex: {}'.format(r))
if swiglpk.glp_get_num_int(self._p) == 0:
self._result = Result(self)
else:
# The intopt MILP solver need an optimal solution to the LP
# relaxation. Therefore, glp_simplex has to run before glp_intopt
# for MILP problems.
logger.debug('Solving using glp_intopt()')
r = swiglpk.glp_intopt(self._p, None)
if r != 0:
raise GLPKError('glp_intopt: {}'.format(r))
self._result = MIPResult(self)
return self._result
def solve_unchecked(self, sense=None):
"""Solve problem and return result.
The user must manually check the status of the result to determine
whether an optimal solution was found. A :class:`SolverError` may still
be raised if the underlying solver raises an exception.
"""
if sense is not None:
self.set_objective_sense(sense)
parm = swiglpk.glp_smcp()
swiglpk.glp_init_smcp(parm)
if self._do_presolve:
parm.presolve = swiglpk.GLP_ON
self._do_presolve = False
else:
parm.presolve = swiglpk.GLP_OFF
parm.tol_bnd = self._feasibility_tolerance
parm.tol_dj = self._optimality_tolerance
logger.debug('Solving using glp_simplex()')
r = swiglpk.glp_simplex(self._p, parm)
if r in (swiglpk.GLP_ENOPFS, swiglpk.GLP_ENODFS):
self._result = Result(self, r)
return self._result
elif r != 0:
raise GLPKError('glp_simplex: {}'.format(r))
if swiglpk.glp_get_num_int(self._p) == 0:
self._result = Result(self)
else:
# The intopt MILP solver needs an optimal solution to the LP
# relaxation. Therefore, glp_simplex has to run before glp_intopt
# for MILP problems.
logger.debug('Solving using glp_intopt()')
parm = swiglpk.glp_iocp()
swiglpk.glp_init_iocp(parm)
parm.tol_int = self._integrality_tolerance
r = swiglpk.glp_intopt(self._p, parm)
if r != 0:
raise GLPKError('glp_intopt: {}'.format(r))
self._result = MIPResult(self)
return self._result
def _optimize(self):
status = self._run_glp_simplex()
if status == interface.UNDEFINED and self.configuration.presolve is True:
# If presolve is on, status will be undefined if not optimal
self.configuration.presolve = False
status = self._run_glp_simplex()
self.configuration.presolve = True
if (glp_get_num_int(self.problem) + glp_get_num_bin(self.problem)) > 0:
status = self._run_glp_mip()
if status == 'undefined' or status == 'infeasible':
# Let's see if the presolver and some scaling can fix this issue
glp_scale_prob(self.problem, GLP_SF_AUTO)
original_presolve_setting = self.configuration.presolve
self.configuration.presolve = True
status = self._run_glp_mip()
self.configuration.presolve = original_presolve_setting
self._status = status
return status
def _optimize(self):
status = self._run_glp_simplex()
# Sometimes GLPK gets itself stuck with an invalid basis. This will help it get rid of it.
if status == interface.UNDEFINED and self.configuration.presolve is not True:
glp_adv_basis(self.problem, 0)
status = self._run_glp_simplex()
if status == interface.UNDEFINED and self.configuration.presolve is True:
# If presolve is on, status will be undefined if not optimal
self.configuration.presolve = False
status = self._run_glp_simplex()
self.configuration.presolve = True
if (glp_get_num_int(self.problem) + glp_get_num_bin(self.problem)) > 0:
status = self._run_glp_mip()
if status == 'undefined' or status == 'infeasible':
# Let's see if the presolver and some scaling can fix this issue
glp_scale_prob(self.problem, GLP_SF_AUTO)
original_presolve_setting = self.configuration.presolve
self.configuration.presolve = True
status = self._run_glp_mip()
self.configuration.presolve = original_presolve_setting
return status
def _optimize(self):
status = self._run_glp_simplex()
# Sometimes GLPK gets itself stuck with an invalid basis. This will help it get rid of it.
if status == interface.UNDEFINED and self.configuration.presolve is not True:
glp_adv_basis(self.problem, 0)
status = self._run_glp_simplex()
if status == interface.UNDEFINED and self.configuration.presolve is True:
# If presolve is on, status will be undefined if not optimal
self.configuration.presolve = False
status = self._run_glp_simplex()
self.configuration.presolve = True
if (glp_get_num_int(self.problem) + glp_get_num_bin(self.problem)) > 0:
status = self._run_glp_mip()
if status == 'undefined' or status == 'infeasible':
# Let's see if the presolver and some scaling can fix this issue
glp_scale_prob(self.problem, GLP_SF_AUTO)
original_presolve_setting = self.configuration.presolve
self.configuration.presolve = True
status = self._run_glp_mip()
self.configuration.presolve = original_presolve_setting
return status
def _glpk_is_mip(self):
return glp_get_num_int(self.problem) > 0
def value(self):
if (glp_get_num_int(self.problem.problem) +
glp_get_num_bin(self.problem.problem)) > 0:
return glp_mip_obj_val(self.problem.problem)
else:
return glp_get_obj_val(self.problem.problem)
def value(self):
if (glp_get_num_int(self.problem.problem) + glp_get_num_bin(self.problem.problem)) > 0:
return glp_mip_obj_val(self.problem.problem)
else:
return glp_get_obj_val(self.problem.problem)
def _glpk_is_mip(self):
return glp_get_num_int(self.problem) > 0
