def optimize(
self,
optName,
tol,
optOptions={},
storeHistory=False,
setDV=None,
xScale=1.0,
objScale=1.0,
conScale=1.0,
offset=0.0,
check_solution=True,
):
# Optimization Object
optProb = Optimization("HS071 Constraint Problem", self.objfunc)
# Design Variables
x0 = [1.0, 5.0, 5.0, 1.0]
optProb.addVarGroup("xvars", 4, lower=1, upper=5, value=x0, scale=xScale, offset=offset)
# Constraints
optProb.addConGroup("con", 2, lower=[25, 40], upper=[None, 40], scale=conScale)
# Objective
optProb.addObj("obj", scale=objScale)
# Optimizer
try:
opt = OPT(optName, options=optOptions)
except Error:
raise unittest.SkipTest("Optimizer not available:", optName)
if isinstance(setDV, str):
optProb.setDVsFromHistory(setDV)
elif isinstance(setDV, dict):
optProb.setDVs(setDV)
outDV = optProb.getDVs()
assert_allclose(setDV["xvars"], outDV["xvars"])
sol = opt(optProb, sens=self.sens, storeHistory=storeHistory)
# Check Solution
if check_solution:
self.fStar = 17.0140172
self.xStar = (1.0, 4.743, 3.82115, 1.37941)
self.lambdaStar = (0.55229366, -0.16146857)
assert_allclose(sol.objectives["obj"].value, self.fStar, atol=tol, rtol=tol)
assert_allclose(sol.xStar["xvars"], self.xStar, atol=tol, rtol=tol)
if hasattr(sol, "lambdaStar"):
assert_allclose(sol.lambdaStar["con"], self.lambdaStar, atol=tol, rtol=tol)
return sol
MP.setObjCon(objCon)
MP.setOptProb(optProb)
# ==============================================================================
# Run optimization
# ==============================================================================
# Create optimizer
optOptions = {
'Function precision': 1e-4,
'Major feasibility tolerance': 1.0e-4,
'Major optimality tolerance': 1.0e-4,
'Difference interval': 1e-3,
'Print file': os.path.join(outputDirectory, 'SNOPT_print.out'),
'Summary file': os.path.join(outputDirectory, 'SNOPT_summary.out'),
}
opt = OPT('snopt', options=optOptions)
# Load the optimized structural variables
optProb.setDVsFromHistory('struct.hst')
# Print Optimization Problem and sparsity
if comm.rank == 0:
print(optProb)
optProb.printSparsity()
# Run Optimization
histFile = os.path.join(outputDirectory, 'opt_hist.hst')
MP.gcomm.barrier()
sol = opt(optProb, MP.sens, storeHistory=histFile)
if comm.rank == 0:
print(sol)
