Add addExprNonlinear

CHANGELOG.md

@@ -1,7 +1,8 @@
 # CHANGELOG
 
-## Unreleased
+## 4.4.0 - 2023-12-04
 ### Added
+- Added SCIP function addExprNonlinear
 - Add support for Cython 3
 - Added methods for getting the names of the current stage and of an event
 ### Fixed

src/pyscipopt/scip.pxi

@@ -258,7 +258,7 @@
     if rc == SCIP_OKAY:
         pass
     elif rc == SCIP_ERROR:
         raise Exception('SCIP: unspecified error!')
     elif rc == SCIP_NOMEMORY:
         raise MemoryError('SCIP: insufficient memory error!')
     elif rc == SCIP_READERROR:
@@ -2365,6 +2365,7 @@
         free(monomials)
         free(termcoefs)
         return PyCons
+
 
     def _addGenNonlinearCons(self, ExprCons cons, **kwargs):
         cdef SCIP_EXPR** childrenexpr
@@ -2489,6 +2490,24 @@
 
         return PyCons
 
+    # TODO Find a better way to retrieve a scip expression from a python expression. Consider making GenExpr include Expr, to avoid using Union. See PR #760.
+    from typing import Union
+    def addExprNonlinear(self, Constraint cons, expr: Union[Expr,GenExpr], float coef):
+        """
+        Add coef*expr to nonlinear constraint.
+        """
+        assert self.getStage() == 1, "addExprNonlinear cannot be called in stage %i." % self.getStage()
+        assert cons.isNonlinear(), "addExprNonlinear can only be called with nonlinear constraints."
+
+        cdef Constraint temp_cons
+        cdef SCIP_EXPR* scip_expr 
+
+        temp_cons = self.addCons(expr <= 0)
+        scip_expr = SCIPgetExprNonlinear(temp_cons.scip_cons)
+
+        PY_SCIP_CALL(SCIPaddExprNonlinear(self._scip, cons.scip_cons, scip_expr, coef))
+        self.delCons(temp_cons)
+
     def addConsCoeff(self, Constraint cons, Variable var, coeff):
         """Add coefficient to the linear constraint (if non-zero).
 

tests/test_nonlinear.py

@@ -284,4 +284,22 @@ def test_quad_coeffs():
     assert quadterms[0][1] == 0.5
 
     assert linterms[0][0].name == z.name
-    assert linterms[0][1] == 4
+    assert linterms[0][1] == 4
+
+def test_addExprNonLinear():
+    m = Model()
+    x = m.addVar("x", lb=0, ub=1, obj=10)
+    y = m.addVar("y", obj=1)
+    z = m.addVar("z", obj=1)
+
+    c = m.addCons(x**2 >= 9)
+    c1 = m.addCons(x**3 >= 4)
+    m.addExprNonlinear(c, y**2, 2)
+    m.addExprNonlinear(c1, z**(1/3), 1)
+
+    m.setParam("numerics/epsilon", 10**(-5)) # bigger eps due to nonlinearities
+    m.optimize()
+
+    assert m.getNSols() > 0
+    assert m.isEQ(m.getVal(y), 2)
+    assert m.isEQ(m.getVal(z), 27)