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Finish TSP implementation; improve performance of Extractors

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Alinson S. Xavier
2020-02-25 22:31:03 -06:00
parent b1f674fcc6
commit 0b04fa93da
33 changed files with 1347 additions and 679 deletions
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17
miplearn/problems/tsp.py
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@@ -25,6 +25,7 @@ class ChallengeA:
n=randint(low=350, high=351),
gamma=uniform(loc=0.95, scale=0.1),
fix_cities=True,
round=True,
)
np.random.seed(seed + 1)
@@ -126,13 +127,13 @@ class TravelingSalesmanInstance(Instance):
self.distances = distances
def to_model(self):
self.model = model = pe.ConcreteModel()
self.edges = edges = [(i,j)
model = pe.ConcreteModel()
model.edges = edges = [(i,j)
for i in range(self.n_cities)
for j in range(i+1, self.n_cities)]
model.x = pe.Var(edges, domain=pe.Binary)
model.obj = pe.Objective(rule=lambda m : sum(m.x[i,j] * self.distances[i,j]
for (i,j) in edges),
model.obj = pe.Objective(expr=sum(model.x[i,j] * self.distances[i,j]
for (i,j) in edges),
sense=pe.minimize)
model.eq_degree = pe.ConstraintList()
model.eq_subtour = pe.ConstraintList()
@@ -144,14 +145,14 @@ class TravelingSalesmanInstance(Instance):
def get_instance_features(self):
return np.array([1])
def get_variable_features(self, var, index):
def get_variable_features(self, var_name, index):
return np.array([1])
def get_variable_category(self, var, index):
def get_variable_category(self, var_name, index):
return index
def find_violations(self, model):
selected_edges = [e for e in self.edges if model.x[e].value > 0.5]
selected_edges = [e for e in model.edges if model.x[e].value > 0.5]
graph = nx.Graph()
graph.add_edges_from(selected_edges)
components = [frozenset(c) for c in list(nx.connected_components(graph))]
@@ -162,7 +163,7 @@ class TravelingSalesmanInstance(Instance):
return violations
def build_lazy_constraint(self, model, component):
cut_edges = [e for e in self.edges
cut_edges = [e for e in model.edges
if (e[0] in component and e[1] not in component) or
(e[0] not in component and e[1] in component)]
return model.eq_subtour.add(sum(model.x[e] for e in cut_edges) >= 2)