Implement TSP generator and LazyConstraintsComponent

miplearn/components/branching.py

@@ -118,29 +118,3 @@ class BranchPriorityComponent(Component):
         instance_features = instance.get_instance_features()
         var_features = instance.get_variable_features(var, index)
         return np.hstack([instance_features, var_features])
-            
-    def merge(self, other_components):
-        keys = set(self.x_train.keys())
-        for comp in other_components:
-            self.pending_instances += comp.pending_instances
-            keys = keys.union(set(comp.x_train.keys()))
-            
-        # Merge x_train and y_train
-        for key in keys:
-            x_train_submatrices = [comp.x_train[key]
-                                   for comp in other_components
-                                   if key in comp.x_train.keys()]
-            y_train_submatrices = [comp.y_train[key]
-                                   for comp in other_components
-                                   if key in comp.y_train.keys()]
-            if key in self.x_train.keys():
-                x_train_submatrices += [self.x_train[key]]
-                y_train_submatrices += [self.y_train[key]]
-            self.x_train[key] = np.vstack(x_train_submatrices)
-            self.y_train[key] = np.vstack(y_train_submatrices)
-            
-        # Merge trained ML predictors
-        for comp in other_components:
-            for key in comp.predictors.keys():
-                if key not in self.predictors.keys():
-                    self.predictors[key] = comp.predictors[key]

miplearn/components/component.py

@@ -18,10 +18,6 @@ class Component(ABC):
     def after_solve(self, solver, instance, model):
         pass
     
-    @abstractmethod
-    def merge(self, other):
-        pass
-    
     @abstractmethod
     def fit(self, training_instances):
         pass

miplearn/components/lazy.py

@@ -0,0 +1,48 @@
+#  MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
+#  Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+#  Released under the modified BSD license. See COPYING.md for more details.
+
+from .component import Component
+from ..extractors import *
+
+from abc import ABC, abstractmethod
+from copy import deepcopy
+import numpy as np
+from sklearn.pipeline import make_pipeline
+from sklearn.linear_model import LogisticRegression
+from sklearn.preprocessing import StandardScaler
+from sklearn.model_selection import cross_val_score
+from sklearn.metrics import roc_curve
+from sklearn.neighbors import KNeighborsClassifier
+from tqdm.auto import tqdm
+import pyomo.environ as pe
+import logging
+logger = logging.getLogger(__name__)
+
+
+class LazyConstraintsComponent(Component):
+    """
+    A component that predicts which lazy constraints to enforce.
+    """
+    
+    def __init__(self):
+        self.violations = set()
+    
+    def before_solve(self, solver, instance, model):
+        logger.info("Enforcing %d lazy constraints" % len(self.violations))
+        for v in self.violations:
+            cut = instance.build_lazy_constraint(model, v)
+            solver.internal_solver.add_constraint(cut)
+        
+    def after_solve(self, solver, instance, model):
+        pass
+                
+    def fit(self, training_instances):
+        for instance in training_instances:
+            if not hasattr(instance, "found_violations"):
+                continue
+            for v in instance.found_violations:
+                self.violations.add(v)
+                
+    def predict(self, instance, model=None):
+        return self.violations

miplearn/components/objective.py

@@ -30,9 +30,6 @@ class ObjectiveValueComponent(Component):
     def after_solve(self, solver, instance, model):
         pass
     
-    def merge(self, other):
-        pass
-    
     def fit(self, training_instances):
         features = InstanceFeaturesExtractor().extract(training_instances)
         ub = ObjectiveValueExtractor(kind="upper bound").extract(training_instances)

miplearn/components/primal.py

@@ -200,6 +200,3 @@ class PrimalSolutionComponent(Component):
                     if ws[i, 1] >= self.thresholds[category, label]:
                         solution[var][index] = label
         return solution
-
-    def merge(self, other_components):
-        pass