feat: branch and perform obbt only on quadratic vars

Author: fracek

galini/branch_and_cut/bound_reduction.py

@@ -18,6 +18,7 @@
 import numpy as np
 import pyomo.environ as pe
 from coramin.relaxations.iterators import relaxation_data_objects
+from galini.branch_and_cut.branching import BILINEAR_RELAXATIONS_TYPES
 from galini.math import is_close
 from galini.pyomo import safe_set_bounds
 from galini.pyomo.util import update_solver_options
@@ -72,13 +73,14 @@ def perform_obbt_on_model(solver, model, linear_model, upper_bound, timelimit, r
     # collect variables in nonlinear constraints
     nonlinear_variables = ComponentSet()
     for relaxation in relaxation_data_objects(linear_model, active=True, descend_into=True):
-        for var in relaxation.get_rhs_vars():
-            # Coramin will complain about variables that are fixed
-            if not var.has_lb() or not var.has_ub():
-                nonlinear_variables.add(var)
-            else:
-                if not np.abs(var.ub - var.lb) < mc.epsilon:
+        if not isinstance(relaxation, BILINEAR_RELAXATIONS_TYPES):
+            for var in relaxation.get_rhs_vars():
+                # Coramin will complain about variables that are fixed
+                if not var.has_lb() or not var.has_ub():
                     nonlinear_variables.add(var)
+                else:
+                    if not np.abs(var.ub - var.lb) < mc.epsilon:
+                        nonlinear_variables.add(var)
 
     time_left = timelimit - seconds_elapsed_since(obbt_start_time)
     nonlinear_variables = list(nonlinear_variables)
@@ -140,6 +142,8 @@ def perform_obbt_on_model(solver, model, linear_model, upper_bound, timelimit, r
 
     for var, new_lb, new_ub in zip(nonlinear_variables, *result):
         original_var = model.find_component(var.getname(fully_qualified=True))
+        if original_var is None:
+            continue
         new_lb = best_lower_bound(var, new_lb, var.lb, eps)
         new_ub = best_upper_bound(var, new_ub, var.ub, eps)
         if np.abs(new_ub - new_lb) < eps:

galini/branch_and_cut/branching.py

@@ -16,6 +16,7 @@
 
 import numpy as np
 import pyomo.environ as pe
+from coramin.relaxations.mccormick import PWMcCormickRelaxation
 
 from galini.branch_and_bound.branching import BranchingPoint
 from galini.branch_and_bound.strategy import BranchingStrategy
@@ -24,6 +25,9 @@
 from galini.math import is_close, is_inf
 
 
+BILINEAR_RELAXATIONS_TYPES = (PWMcCormickRelaxation,)
+
+
 class BranchAndCutBranchingStrategy(BranchingStrategy):
     def __init__(self, algorithm):
         pass
@@ -162,6 +166,8 @@ def compute_nonlinear_infeasiblity_components(linear_problem, mip_solution):
         }
 
     for relaxation in linear_problem.galini_nonlinear_relaxations:
+        if not isinstance(relaxation, BILINEAR_RELAXATIONS_TYPES):
+            continue
         rhs_vars = relaxation.get_rhs_vars()
 
         if len(rhs_vars) > 2:

galini/branch_and_cut/node_storage.py

@@ -19,9 +19,9 @@
 from pyomo.contrib.fbbt.fbbt import compute_bounds_on_expr
 
 from galini.branch_and_bound.branching import branch_at_point
-from galini.relaxations.relax import RelaxationData
 from galini.cuts.pool import CutNodeStorage, CutPool
 from galini.pyomo import safe_setlb, safe_setub
+from galini.relaxations.relax import RelaxationData
 
 
 class BranchingDecision:

galini/relaxations/expressions.py

@@ -15,14 +15,11 @@
 """Functions to relax nonlinear pyomo expresions."""
 
 import networkx as nx
-
-from suspect.pyomo.quadratic import QuadraticExpression
-import pyomo.environ as pe
-from suspect.convexity.rules.quadratic import QuadraticRule
-from pyomo.contrib.fbbt.fbbt import compute_bounds_on_expr
-from coramin.utils.coramin_enums import RelaxationSide, FunctionShape
+from coramin.utils.coramin_enums import RelaxationSide
 from galini.relaxations.multivariate import FactorableConvexExpressionRelaxation
-from coramin.relaxations.auto_relax import replace_sub_expression_with_aux_var
+from pyomo.contrib.fbbt.fbbt import compute_bounds_on_expr
+from suspect.convexity.rules.quadratic import QuadraticRule
+from suspect.pyomo.quadratic import QuadraticExpression
 
 _convexity_rule = QuadraticRule()
 

galini/relaxations/multivariate.py

@@ -14,13 +14,13 @@
 
 """Relaxation that replaces a convex function with an auxiliary variable."""
 
-from coramin.utils.coramin_enums import RelaxationSide, FunctionShape
+import math
+
+import pyomo.environ as pe
 from coramin.relaxations.custom_block import declare_custom_block
 from coramin.relaxations.relaxations_base import BaseRelaxationData, ComponentWeakRef
+from coramin.utils.coramin_enums import RelaxationSide
 from pyomo.core.expr.visitor import identify_variables
-import math
-import pyomo.environ as pe
-from coramin.relaxations._utils import _get_bnds_list
 
 
 @declare_custom_block(name='FactorableConvexExpressionRelaxation')

galini/relaxations/relax.py

@@ -21,6 +21,7 @@
     _relax_root_to_leaf_SumExpression,
     _relax_expr,
 )
+from coramin.relaxations import PWXSquaredRelaxation, PWUnivariateRelaxation
 from coramin.utils.coramin_enums import RelaxationSide
 from pyomo.core.expr.numvalue import polynomial_degree
 from suspect.pyomo.quadratic import QuadraticExpression
@@ -164,7 +165,7 @@ def relax(model, data, use_linear_relaxation=True):
 
         assert obj.is_minimizing()
 
-        relaxation_side = RelaxationSide.UNDER
+        # relaxation_side = RelaxationSide.UNDER
         relaxation_side = RelaxationSide.BOTH
 
         new_body = relax_expression(model, obj.expr, relaxation_side, data)