Adjusting mps writer to the correct structure regarding integer variables declaration

pyomo/repn/plugins/mps.py

@@ -515,10 +515,22 @@ def yield_all_constraints():
         column_template = "     %s %s %" + self._precision_string + "\n"
         output_file.write("COLUMNS\n")
         cnt = 0
+        set_integer = False
         for vardata in variable_list:
             col_entries = column_data[variable_to_column[vardata]]
             cnt += 1
             if len(col_entries) > 0:
+                if vardata.is_integer() and not set_integer:
+                    set_integer = True
+                    output_file.write(
+                        "     %s %s %s\n" % ("INT", "'MARKER'", "'INTORG'")
+                    )
+                if not vardata.is_integer() and set_integer:
+                    set_integer = False
+                    output_file.write(
+                        "     %s %s %s\n" % ("INTEND", "'MARKER'", "'INTEND'")
+                    )
+
                 var_label = variable_symbol_dictionary[id(vardata)]
                 for i, (row_label, coef) in enumerate(col_entries):
                     output_file.write(

pyomo/repn/tests/mps/integer_variable_declaration.mps.baseline

@@ -0,0 +1,27 @@
+* Source:     Pyomo MPS Writer
+* Format:     Free MPS
+*
+NAME Example-mix-integer-linear-problem
+OBJSENSE
+ MIN
+ROWS
+ N  obj
+ G  c_l_const1_
+ L  c_u_const2_
+COLUMNS
+     INT 'MARKER' 'INTORG'
+     x1 obj 3
+     x1 c_l_const1_ 4
+     x1 c_u_const2_ 1
+     INTEND 'MARKER' 'INTEND'
+     x2 obj 2
+     x2 c_l_const1_ 3
+     x2 c_u_const2_ 2
+RHS
+     RHS c_l_const1_ 10
+     RHS c_u_const2_ 7
+BOUNDS
+ LI BOUND x1 0
+ UI BOUND x1 10E20
+ LO BOUND x2 0
+ENDATA

pyomo/repn/tests/mps/knapsack_problem_binary_variable_declaration.mps.baseline

@@ -0,0 +1,39 @@
+* Source:     Pyomo MPS Writer
+* Format:     Free MPS
+*
+NAME knapsack problem
+OBJSENSE
+ MIN
+ROWS
+ N  obj
+ G  c_l_const1_
+COLUMNS
+     INT 'MARKER' 'INTORG'
+     x(_1_) obj 3
+     x(_1_) c_l_const1_ 30
+     x(_2_) obj 2
+     x(_2_) c_l_const1_ 24
+     x(_3_) obj 2
+     x(_3_) c_l_const1_ 11
+     x(_4_) obj 4
+     x(_4_) c_l_const1_ 35
+     x(_5_) obj 5
+     x(_5_) c_l_const1_ 29
+     x(_6_) obj 4
+     x(_6_) c_l_const1_ 8
+     x(_7_) obj 3
+     x(_7_) c_l_const1_ 31
+     x(_8_) obj 1
+     x(_8_) c_l_const1_ 18
+RHS
+     RHS c_l_const1_ 60
+BOUNDS
+ BV BOUND x(_1_)
+ BV BOUND x(_2_)
+ BV BOUND x(_3_)
+ BV BOUND x(_4_)
+ BV BOUND x(_5_)
+ BV BOUND x(_6_)
+ BV BOUND x(_7_)
+ BV BOUND x(_8_)
+ENDATA

pyomo/repn/tests/mps/test_mps.py

@@ -18,7 +18,17 @@
 from filecmp import cmp
 import pyomo.common.unittest as unittest
 
-from pyomo.environ import ConcreteModel, Var, Objective, Constraint, ComponentMap
+from pyomo.environ import (
+    ConcreteModel,
+    Var,
+    Objective,
+    Constraint,
+    ComponentMap,
+    minimize,
+    Binary,
+    NonNegativeReals,
+    NonNegativeIntegers,
+)
 
 thisdir = os.path.dirname(os.path.abspath(__file__))
 
@@ -41,6 +51,7 @@ def _check_baseline(self, model, **kwds):
         io_options = {"symbolic_solver_labels": True}
         io_options.update(kwds)
         model.write(test_fname, format="mps", io_options=io_options)
+
         self.assertTrue(
             cmp(test_fname, baseline_fname),
             msg="Files %s and %s differ" % (test_fname, baseline_fname),
@@ -185,6 +196,52 @@ def test_row_ordering(self):
         row_order[model.con4[2]] = -1
         self._check_baseline(model, row_order=row_order)
 
+    def test_knapsack_problem_binary_variable_declaration(self):
+        elements_size = [30, 24, 11, 35, 29, 8, 31, 18]
+        elements_weight = [3, 2, 2, 4, 5, 4, 3, 1]
+        capacity = 60
+
+        model = ConcreteModel("knapsack problem")
+        var_names = [f"{i + 1}" for i in range(len(elements_size))]
+
+        model.x = Var(var_names, within=Binary)
+
+        model.obj = Objective(
+            expr=sum(
+                model.x[var_names[i]] * elements_weight[i]
+                for i in range(len(elements_size))
+            ),
+            sense=minimize,
+            name="obj",
+        )
+
+        model.const1 = Constraint(
+            expr=sum(
+                model.x[var_names[i]] * elements_size[i]
+                for i in range(len(elements_size))
+            )
+            >= capacity,
+            name="const",
+        )
+
+        self._check_baseline(model)
+
+    def test_integer_variable_declaration(self):
+        model = ConcreteModel("Example-mix-integer-linear-problem")
+
+        # Define the decision variables
+        model.x1 = Var(within=NonNegativeIntegers)  # Integer variable
+        model.x2 = Var(within=NonNegativeReals)  # Continuous variable
+
+        # Define the objective function
+        model.obj = Objective(expr=3 * model.x1 + 2 * model.x2, sense=minimize)
+
+        # Define the constraints
+        model.const1 = Constraint(expr=4 * model.x1 + 3 * model.x2 >= 10)
+        model.const2 = Constraint(expr=model.x1 + 2 * model.x2 <= 7)
+
+        self._check_baseline(model)
+
 
 if __name__ == "__main__":
     unittest.main()