def run(**kwargs):
simulation = simCSTR()
nlpsolver = pyIPOPT.daeIPOPT()
return daeActivity.optimize(simulation,
reportingInterval=600,
timeHorizon=5 * 60 * 60,
nlpsolver=nlpsolver,
nlpsolver_setoptions_fn=setOptions,
reportSensitivities=True,
**kwargs)
def run(**kwargs):
simulation = simTutorial()
# Achtung! Achtung! NLP solver options can only be set after optimization.Initialize()
# Otherwise seg. fault occurs for some reasons.
nlpsolver = pyIPOPT.daeIPOPT()
return daeActivity.optimize(simulation,
reportingInterval=1,
timeHorizon=1,
nlpsolver=nlpsolver,
nlpsolver_setoptions_fn=setOptions,
reportSensitivities=True,
**kwargs)
def run(**kwargs):
simulation = simCatalystMixing(200, 1.0 / 200)
nlpsolver = pyIPOPT.daeIPOPT()
lasolver = pyTrilinos.daeCreateTrilinosSolver("Amesos_Klu", "")
relativeTolerance = 1e-6
return daeActivity.optimize(simulation,
reportingInterval=1,
timeHorizon=1,
lasolver=lasolver,
nlpsolver=nlpsolver,
nlpsolver_setoptions_fn=setOptions,
relativeTolerance=relativeTolerance,
**kwargs)
def createNLPSolver(minlpsolverIndex):
nlpsolver = None
if minlpsolverIndex == nlpIPOPT:
from daetools.solvers.ipopt import pyIPOPT
nlpsolver = pyIPOPT.daeIPOPT()
elif minlpsolverIndex == nlpNLOPT:
from daetools.solvers.nlopt import pyNLOPT
# Default algorithm
algorithm = 'NLOPT_LD_SLSQP'
try:
from PyQt5 import QtCore, QtGui
algorithms = [
'NLOPT_GN_DIRECT', 'NLOPT_GN_DIRECT_L',
'NLOPT_GN_DIRECT_L_RAND', 'NLOPT_GN_DIRECT_NOSCAL',
'NLOPT_GN_DIRECT_L_NOSCAL', 'NLOPT_GN_DIRECT_L_RAND_NOSCAL',
'NLOPT_GN_ORIG_DIRECT', 'NLOPT_GN_ORIG_DIRECT_L',
'NLOPT_GD_STOGO', 'NLOPT_GD_STOGO_RAND',
'NLOPT_LD_LBFGS_NOCEDAL', 'NLOPT_LD_LBFGS', 'NLOPT_LN_PRAXIS',
'NLOPT_LD_VAR1', 'NLOPT_LD_VAR2', 'NLOPT_LD_TNEWTON',
'NLOPT_LD_TNEWTON_RESTART', 'NLOPT_LD_TNEWTON_PRECOND',
'NLOPT_LD_TNEWTON_PRECOND_RESTART', 'NLOPT_GN_CRS2_LM',
'NLOPT_GN_MLSL', 'NLOPT_GD_MLSL', 'NLOPT_GN_MLSL_LDS',
'NLOPT_GD_MLSL_LDS', 'NLOPT_LD_MMA', 'NLOPT_LN_COBYLA',
'NLOPT_LN_NEWUOA', 'NLOPT_LN_NEWUOA_BOUND',
'NLOPT_LN_NELDERMEAD', 'NLOPT_LN_SBPLX', 'NLOPT_LN_AUGLAG',
'NLOPT_LD_AUGLAG', 'NLOPT_LN_AUGLAG_EQ', 'NLOPT_LD_AUGLAG_EQ',
'NLOPT_LN_BOBYQA', 'NLOPT_GN_ISRES', 'NLOPT_AUGLAG',
'NLOPT_AUGLAG_EQ', 'NLOPT_G_MLSL', 'NLOPT_G_MLSL_LDS',
'NLOPT_LD_SLSQP'
]
# Show the input box to choose the algorithm (the default is len(algorithms)-1 that is: NLOPT_LD_SLSQP)
algorithm, ok = QtGui.QInputDialog.getItem(
None, "NLOPT Algorithm", "Choose the NLOPT algorithm:",
algorithms,
len(algorithms) - 1, False)
except Exception as e:
pass
nlpsolver = pyNLOPT.daeNLOPT(str(algorithm))
elif minlpsolverIndex == nlpBONMIN:
from daetools.solvers.bonmin import pyBONMIN
nlpsolver = pyBONMIN.daeBONMIN()
else:
raise RuntimeError("Unsupported (MI)NLP Solver selected")
return nlpsolver
def run(**kwargs):
simulation = simOilCracking_opt()
nlpsolver = pyIPOPT.daeIPOPT()
lasolver = pyTrilinos.daeCreateTrilinosSolver("Amesos_Klu", "")
relativeTolerance = 1e-6
reportingTimes = times.tolist()
return daeActivity.optimize(simulation,
reportingInterval=1,
timeHorizon=1,
reportingTimes=reportingTimes,
lasolver=lasolver,
nlpsolver=nlpsolver,
nlpsolver_setoptions_fn=setOptions,
relativeTolerance=relativeTolerance,
**kwargs)
def run(**kwargs):
simulation = simMarinePopulation_opt()
#nlpsolver = pyNLOPT.daeNLOPT('NLOPT_LD_SLSQP')
nlpsolver = pyIPOPT.daeIPOPT()
lasolver = pyTrilinos.daeCreateTrilinosSolver("Amesos_Klu", "")
relativeTolerance = 1e-6
reportingTimes = times.tolist()
return daeActivity.optimize(simulation,
reportingInterval=1,
timeHorizon=1,
reportingTimes=reportingTimes,
lasolver=lasolver,
nlpsolver=nlpsolver,
nlpsolver_setoptions_fn=setOptions,
relativeTolerance=relativeTolerance,
reportSensitivities=True,
**kwargs)