Reputation: 1
i tried to optimize a model with pyomo using ipopt. But everytime i try a model following error occurs:
""" ERROR: Solver (ipopt) returned non-zero return code (1) ERROR: Solver log: Ipopt 3.5.5: Unknown keyword "max_cpu_time" constr_viol_tol=1e-08 Traceback (most recent call last):
File "C:\Users\Marvin Lang\Documents\Python Scripts\untitled0.py", line 21, in pe.SolverFactory('mindtpy').solve(model, mip_solver='glpk', nlp_solver='ipopt')
File "C:\Anaconda\lib\site-packages\pyomo\contrib\mindtpy\MindtPy.py", line 113, in solve return SolverFactory(_supported_algorithms[config.strategy][0]).solve(
File "C:\Anaconda\lib\site-packages\pyomo\contrib\mindtpy\algorithm_base_class.py", line 2800, in solve self.MindtPy_initialization(config)
File "C:\Anaconda\lib\site-packages\pyomo\contrib\mindtpy\algorithm_base_class.py", line 841, in MindtPy_initialization self.init_rNLP(config)
File "C:\Anaconda\lib\site-packages\pyomo\contrib\mindtpy\algorithm_base_class.py", line 877, in init_rNLP results = nlpopt.solve(
File "C:\Anaconda\lib\site-packages\pyomo\opt\base\solvers.py", line 627, in solve raise ApplicationError("Solver (%s) did not exit normally" % self.name)
ApplicationError: Solver (ipopt) did not exit normally """
I also tried a code i found online:
import pyomo.environ as pe
model = pe.ConcreteModel()
model.x = pe.Var(bounds=(1.0,10.0),initialize=5.0) model.y = pe.Var(within=pe.Binary)
model.c1 = pe.Constraint(expr=(model.x-4.0)2 - model.x <= 50.0(1-model.y)) model.c2 = pe.Constraint(expr=model.xpe.log(model.x)+5.0 <= 50.0*(model.y))
model.objective = pe.Objective(expr=model.x, sense=pe.minimize)
pe.SolverFactory('mindtpy').solve(model, mip_solver='glpk', nlp_solver='ipopt')
It would be nice if anybody have an idea about this problem.
I tried different versions of ipopt. Version of Pyomo is 6.6.1
Upvotes: 0
Views: 502
Reputation: 929
max_cpu_time was introduced with Ipopt 3.6.0, so it is an unknown keyword for Ipopt 3.5.5. Update your Ipopt installation.
Upvotes: 0