Alamo Six Hump Camel¶

Notebook

In [1]:

from idaes.surrogate import alamopy
import examples
import pyomo.environ as pyo
from pyutilib.common import ApplicationError
import camel6

In [2]:

alamo_ran = camel6.main()

Updating number of training points from 10 to 10
Model: {'z1': '  z1 =  - 0.14498340626190308193906E-014 * x1 + 0.28519578140053886891354E-014 * x2 + 3.9999999999999955591079 * x1^2 - 3.9999999999999964472863 * x2^2 - 2.0999999999999987565502 * x1^4 + 4.0000000000000044408921 * x2^4 + 0.33333333333333325931847 * x1^6 + 1.0000000000000015543122 * x1*x2'}

In [3]:

hasBaron = False
try:
    solver_opt = pyo.SolverFactory('baron')
    hasBaron = solver_opt.available()
except ApplicationError as err:
    print("Partial test completed. %s"%err)


if alamo_ran and hasBaron:
    model = pyo.ConcreteModel()
    opt = pyo.SolverFactory('baron')
    model.x1 = pyo.Var()
    model.x2 = pyo.Var()
    def pyomo_model(model):
        import z1
        return z1.f(model.x1,model.x2)
    model.obj = pyo.Objective(rule = pyomo_model)
    results = opt.solve(model)
    model.solutions.store_to(results)
    print(results)

Problem: 
- Name: problem
  Lower bound: -1e+51
  Upper bound: -1.03162845349
  Number of objectives: 1
  Number of constraints: 1
  Number of variables: 3
  Sense: unknown
Solver: 
- Status: ok
  Termination condition: unknown
  Error rc: 0
  Time: 0.21648550033569336
Solution: 
- number of solutions: 1
  number of solutions displayed: 1
- Gap: 1e+51
  Status: feasible
  Message: None
  Objective:
    obj:
      Value: -1.0316284534898725
  Variable:
    x1:
      Value: -0.08984201361113409
    x2:
      Value: 0.7126564070725505
  Constraint: No values

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