Fix duplicate-variable coefficients in LinExpr

mip/entities.py

@@ -89,7 +89,17 @@ def __init__(
                     "You should pass eiter 'expr' or 'variables and coeffs' to the"
                     "constructor, not the three simultaneously."
                 )
-            self.__expr = dict(zip(variables, coeffs))
+            # dict(zip(...)) silently drops all but the last coefficient when
+            # the same variable appears more than once, so fall back to an
+            # accumulating loop only when duplicates are actually present.
+            # This keeps the common (duplicate-free) case as fast as before.
+            if len(variables) == len(set(variables)):
+                self.__expr = dict(zip(variables, coeffs))
+            else:
+                expr_dict = {}  # type: dict[mip.Var, mip.Numeric]
+                for var, coeff in zip(variables, coeffs):
+                    expr_dict[var] = expr_dict.get(var, 0) + coeff
+                self.__expr = expr_dict
 
         elif expr is not None:
             self.__expr = expr.copy()

test/mip_test.py

@@ -7,6 +7,7 @@
 import mip.gurobi
 import mip.highs
 from mip import Model, xsum, OptimizationStatus, MAXIMIZE, BINARY, INTEGER
+from mip.entities import LinExpr
 from mip import ConstrsGenerator, CutPool, maximize, CBC, GUROBI, HIGHS, Column, Constr
 from os import environ
 from util import skip_on, has_gurobi_license
@@ -588,6 +589,43 @@ def test_obj_const2(self, solver: str):
         assert model.objective_const == 1
 
 
+@skip_on(NotImplementedError)
+@pytest.mark.parametrize("solver", SOLVERS)
+@pytest.mark.parametrize(
+    "constraint, lb, ub",
+    [
+        (lambda x: x + x >= 3, 1, 2),
+        (lambda x: x - x >= 0, 1, 2),
+        (lambda x: x == x, 1, 2),
+        (lambda x: x >= x, 1, 2),
+        (lambda x: x <= x, -2, -1),
+        (lambda x: LinExpr([x, x, x], [2, -1, -1], sense="="), 1, 2),
+    ],
+)
+def test_identical_vars(solver: str, constraint, lb, ub):
+    """Try if constraints are correctly added when variables are identical"""
+    m = Model(solver_name=solver)
+    x = m.add_var(name="x", lb=lb, ub=ub, obj=1)
+
+    m.add_constr(constraint(x))
+
+    m.optimize()
+    assert m.status == OptimizationStatus.OPTIMAL
+    assert lb - TOL <= x.x <= ub + TOL
+
+
+def test_linexpr_duplicate_variables_constructor():
+    """LinExpr constructed directly with duplicate variables should sum
+    coefficients instead of silently dropping earlier ones (issue #396)."""
+    m = Model()
+    x = m.add_var(name="x")
+    y = m.add_var(name="y")
+
+    expr = LinExpr([x, y, x], [1, 2, 3])
+    assert expr.expr[x] == 4
+    assert expr.expr[y] == 2
+
+
 @skip_on(NotImplementedError)
 @pytest.mark.parametrize("val", range(1, 4))
 @pytest.mark.parametrize("solver", SOLVERS)