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Factorable Programming for PWL Approximations #3821

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4863d1f
initial draft of factorable programming transformation for pwl approx…
michaelbynum Jan 17, 2026
4b36753
Merge remote-tracking branch 'origin/main' into pwl_factorable
michaelbynum Jan 20, 2026
c822381
tests for piecewise univariate nonlinear decomposition
michaelbynum Jan 20, 2026
43f5e57
testing for univariate nonlinear decomposition
michaelbynum Jan 20, 2026
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3 changes: 3 additions & 0 deletions pyomo/contrib/piecewise/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -37,6 +37,9 @@
DomainPartitioningMethod,
NonlinearToPWL,
)
from pyomo.contrib.piecewise.transform.factorable import (
UnivariateNonlinearDecompositionTransformation,
)
from pyomo.contrib.piecewise.transform.nested_inner_repn import (
NestedInnerRepresentationGDPTransformation,
)
Expand Down
266 changes: 266 additions & 0 deletions pyomo/contrib/piecewise/tests/test_univariate_nonlinear_decomposition.py
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Original file line number Diff line number Diff line change
@@ -0,0 +1,266 @@
from pyomo.common.unittest import TestCase, skipUnless
import pyomo.environ as pyo
from pyomo.contrib import piecewise
from pyomo.core.expr.compare import assertExpressionsEqual
from pyomo.common.dependencies import numpy_available, numpy
from pyomo.core.expr.numeric_expr import ProductExpression


pe = pyo


def _get_trans():
return pyo.TransformationFactory('contrib.piecewise.univariate_nonlinear_decomposition')


class TestUnivariateNonlinearDecomposition(TestCase):
def test_multiterm(self):
m = pe.ConcreteModel()
m.x = pe.Var()
m.y = pe.Var()
m.z = pe.Var()
m.c = pe.Constraint(expr=m.x + pe.log(m.y + m.z) + 1/pe.exp(m.x**0.5) <= 0)

trans = _get_trans()
trans.apply_to(m)
aux = m.auxiliary

assertExpressionsEqual(
self,
m.c.body,
m.x + aux.x[3] + aux.x[2],
)
assertExpressionsEqual(
self,
aux.c[1].expr,
aux.x[1] == (m.y + m.z),
)
assertExpressionsEqual(
self,
aux.c[2].expr,
aux.x[2] == 1/pyo.exp(m.x**0.5),
)
assertExpressionsEqual(
self,
aux.c[3].expr,
aux.x[3] == pyo.log(aux.x[1]),
)
self.assertEqual(m.x.lb, 0)
self.assertIsNone(m.x.ub)
self.assertIsNone(m.y.lb)
self.assertIsNone(m.y.ub)
self.assertIsNone(m.z.lb)
self.assertIsNone(m.z.ub)
self.assertEqual(aux.x[1].lb, 0)
self.assertIsNone(aux.x[1].ub)
self.assertEqual(aux.x[2].lb, 0)
self.assertEqual(aux.x[2].ub, 1)
self.assertIsNone(aux.x[3].lb)
self.assertIsNone(aux.x[3].ub)

def test_common_subexpressions(self):
m = pe.ConcreteModel()
m.x = pe.Var()
m.y = pe.Var()
m.z1 = pe.Var()
m.z2 = pe.Var()
e = -pe.log(m.x + m.y)
m.c1 = pe.Constraint(expr=m.z1 + e == 0)
m.c2 = pe.Constraint(expr=m.z2 + e == 0)

trans = _get_trans()
trans.apply_to(m)
aux = m.auxiliary

assertExpressionsEqual(
self,
m.c1.expr,
m.z1 + aux.x[2] == 0,
)
assertExpressionsEqual(
self,
m.c2.expr,
m.z2 + aux.x[2] == 0,
)
assertExpressionsEqual(
self,
aux.c[1].expr,
aux.x[1] == m.x + m.y,
)
assertExpressionsEqual(
self,
aux.c[2].expr,
aux.x[2] == -pe.log(aux.x[1]),
)

def test_product_fixed_variable(self):
m = pe.ConcreteModel()
m.x = pe.Var()
m.y = pe.Var()
m.z = pe.Var()
m.c = pe.Constraint(expr=2*pe.log(m.x + m.y) <= 0)

trans = _get_trans()
trans.apply_to(m)
aux = m.auxiliary

assertExpressionsEqual(
self,
m.c.expr,
2*pe.log(aux.x[1]) <= 0,
)
assertExpressionsEqual(
self,
aux.c[1].expr,
aux.x[1] == m.x + m.y,
)

def test_product_variable_fixed(self):
m = pe.ConcreteModel()
m.x = pe.Var()
m.y = pe.Var()
m.z = pe.Var()
m.c = pe.Constraint(expr=pe.log(m.x + m.y)*2 <= 0)

trans = _get_trans()
trans.apply_to(m)
aux = m.auxiliary

assertExpressionsEqual(
self,
m.c.expr,
pe.log(aux.x[1])*2 <= 0,
)
assertExpressionsEqual(
self,
aux.c[1].expr,
aux.x[1] == m.x + m.y,
)

def test_prod_sum_sum(self):
m = pe.ConcreteModel()
m.x1 = pe.Var()
m.x2 = pe.Var()
m.x3 = pe.Var()
m.x4 = pe.Var()
m.c = pe.Constraint(expr=(m.x1 + m.x2) * (m.x3 + m.x4) <= 1)

trans = _get_trans()
trans.apply_to(m)
aux = m.auxiliary

assertExpressionsEqual(
self,
m.c.expr,
aux.x[1] * aux.x[2] <= 1,
)
assertExpressionsEqual(
self,
aux.c[1].expr,
aux.x[1] == m.x1 + m.x2,
)
assertExpressionsEqual(
self,
aux.c[2].expr,
aux.x[2] == m.x3 + m.x4,
)

def test_pow_sum_sum(self):
m = pe.ConcreteModel()
m.x1 = pe.Var()
m.x2 = pe.Var()
m.x3 = pe.Var()
m.x4 = pe.Var()
m.c = pe.Constraint(expr=(m.x1 + m.x2) ** (m.x3 + m.x4) <= 1)

trans = _get_trans()
trans.apply_to(m)
aux = m.auxiliary

assertExpressionsEqual(
self,
m.c.expr,
aux.x[1] ** aux.x[2] <= 1,
)
assertExpressionsEqual(
self,
aux.c[1].expr,
aux.x[1] == m.x1 + m.x2,
)
assertExpressionsEqual(
self,
aux.c[2].expr,
aux.x[2] == m.x3 + m.x4,
)

def test_division_var_const(self):
m = pe.ConcreteModel()
m.x = pe.Var()
m.y = pe.Var()
m.c = pe.Constraint(expr=(m.x + m.y) / 2 <= 0)

trans = _get_trans()
trans.apply_to(m)
aux = m.auxiliary

assertExpressionsEqual(
self,
m.c.expr,
(m.x + m.y) / 2 <= 0,
)

def test_division_sum_sum(self):
m = pe.ConcreteModel()
m.x1 = pe.Var()
m.x2 = pe.Var()
m.x3 = pe.Var()
m.x4 = pe.Var()
m.c = pe.Constraint(expr=(m.x1 + m.x2) / (m.x3 + m.x4) <= 1)

trans = _get_trans()
trans.apply_to(m)
aux = m.auxiliary

assertExpressionsEqual(
self,
m.c.expr,
aux.x[1] * aux.x[3] <= 1,
)
assertExpressionsEqual(
self,
aux.c[1].expr,
aux.x[1] == m.x1 + m.x2,
)
assertExpressionsEqual(
self,
aux.c[2].expr,
aux.x[2] == m.x3 + m.x4,
)
assertExpressionsEqual(
self,
aux.c[3].expr,
aux.x[3] * aux.x[2] == 1,
)

@skipUnless(numpy_available, "Numpy is not available")
def test_numpy_float(self):
m = pe.ConcreteModel()
m.x = pe.Var()
m.y = pe.Var()
m.z = pe.Var()
m.c = pe.Constraint(expr=ProductExpression((numpy.float64(2.5), pe.log(m.x + m.y))) <= 0)

trans = _get_trans()
trans.apply_to(m)
aux = m.auxiliary

assertExpressionsEqual(
self,
m.c.expr,
2.5*pe.log(aux.x[1]) <= 0,
)
assertExpressionsEqual(
self,
aux.c[1].expr,
aux.x[1] == m.x + m.y,
)
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