1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
|
#! /usr/bin/env python
import openturns as ot
ot.TESTPREAMBLE()
ot.PlatformInfo.SetNumericalPrecision(4)
# linear
levelFunction = ot.SymbolicFunction(["x1", "x2", "x3", "x4"], ["x1+2*x2-3*x3+4*x4"])
algo = ot.Cobyla(ot.NearestPointProblem(levelFunction, 3.0))
algo.setStartingPoint([0.0] * 4)
print("algo=", algo)
algo.run()
result = algo.getResult()
print("x^=", result.getOptimalPoint())
print("f(x^)=", result.getOptimalValue())
print("lambda^=", result.computeLagrangeMultipliers())
# non-linear
levelFunction = ot.SymbolicFunction(
["x1", "x2", "x3", "x4"], ["x1*cos(x1)+2*x2*x3-3*x3+4*x3*x4"]
)
algo = ot.Cobyla(ot.NearestPointProblem(levelFunction, 3.0))
algo.setStartingPoint([0.0] * 4)
algo.setMaximumCallsNumber(400)
algo.setMaximumAbsoluteError(1.0e-10)
algo.setMaximumRelativeError(1.0e-10)
algo.setMaximumResidualError(1.0e-10)
algo.setMaximumConstraintError(1.0e-10)
algo.run()
result = algo.getResult()
print("x^=", result.getOptimalPoint())
print("f(x^)=", result.getOptimalValue())
print("lambda^=", result.computeLagrangeMultipliers())
# bounds
linear = ot.SymbolicFunction(["x1", "x2", "x3", "x4"], ["x1+2*x2-3*x3+4*x4"])
dim = 4
bounds = ot.Interval([-3.0] * dim, [5.0] * dim)
for minimization in [True, False]:
problem = ot.OptimizationProblem(linear, ot.Function(), ot.Function(), bounds)
problem.setMinimization(minimization)
algo = ot.Cobyla(problem)
algo.setMaximumCallsNumber(150)
algo.setStartingPoint([0.0] * dim)
print("algo=", algo)
algo.run()
result = algo.getResult()
print("x^=", result.getOptimalPoint())
print("f(x^)=", result.getOptimalValue())
print("lambda^=", result.computeLagrangeMultipliers())
# empty problem
algo = ot.Cobyla()
try:
algo.run()
except Exception:
print("OK")
|
