add use_convex_relaxation option

pyomo/contrib/mindtpy/algorithm_base_class.py

@@ -2155,7 +2155,7 @@ def setup_main(self):
                 * sum(v for v in MindtPy.cuts.slack_vars.values())
             )
         main_objective = MindtPy.objective_list[-1]
-        if not config.use_obbt:
+        if not config.use_convex_relaxation:
             MindtPy.del_component('mip_obj')
             MindtPy.mip_obj = Objective(
                 expr=main_objective.expr
@@ -2402,6 +2402,15 @@ def check_config(self):
         ):
             self.load_solutions = False
 
+        if config.use_obbt:
+            config.use_convex_relaxation = True
+
+        if config.add_slack and config.use_convex_relaxation:
+            raise NotImplementedError(
+                "In current implementation, use_convex_relaxation "
+                "and add_slack cannot be activated at the same time."
+            )
+
     ################################################################################################################################
     # Feasibility Pump
 
@@ -2681,10 +2690,18 @@ def initialize_mip_problem(self):
 
         self.mip = self.working_model.clone()
 
-        # OBBT
-        if config.use_obbt:
+        # Convex relaxation
+        if config.use_convex_relaxation:
             with time_code(self.timing, 'presolve - convex relaxation'):
                 self.mip.coramin_relaxation = coramin.relaxations.relax(self.mip)
+                # If the variable is fixed or have lower bounds equal to their upper bounds, Coramin recognizes that this type of constraint is linear under those conditions and will just return the original constraint.
+                # MindtPy need to manually deactivate the original constraint.
+                for rel in coramin.relaxations.relaxation_data_objects(
+                    self.mip.coramin_relaxation
+                ):
+                    if rel.component("_original_constraint") is not None:
+                        rel._original_constraint.deactivate()
+
                 # TODO: only needed for avm cuts
                 # for rel in coramin.relaxations.relaxation_data_objects(
                 #     self.mip.coramin_relaxation

pyomo/contrib/mindtpy/config_options.py

@@ -462,10 +462,18 @@ def _add_common_configs(CONFIG):
             domain=bool,
         ),
     )
+    CONFIG.declare(
+        'use_convex_relaxation',
+        ConfigValue(
+            default=False,
+            description='Use convex relaxation to tighten the feasible region of the problem.',
+            domain=bool,
+        ),
+    )
     CONFIG.declare(
         'use_obbt',
         ConfigValue(
-            default=True,
+            default=False,
             description='Use obbt to tighten the feasible region of the problem.',
             domain=bool,
         ),

pyomo/contrib/mindtpy/outer_approximation.py

@@ -91,7 +91,7 @@ def check_config(self):
                 'sqp_lag',
             }:
                 self.regularization_mip_type = 'MIQP'
-        _MindtPyAlgorithm.check_config(self)
+        super().check_config()
 
     def initialize_mip_problem(self):
         """Deactivate the nonlinear constraints to create the MIP problem."""