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tsp: Remove some code duplication

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This commit is contained in:
Alinson S. Xavier
2024-01-30 16:32:39 -06:00
parent 25bbe20748
commit 2774edae8c
1 changed files with 24 additions and 29 deletions
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53
miplearn/problems/tsp.py
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@@ -149,21 +149,8 @@ def build_tsp_model_gurobipy(
)
def lazy_separate(model: GurobiModel) -> List[Any]:
violations = []
x = model.inner.cbGetSolution(model.inner._x)
selected_edges = [e for e in model.inner._edges if x[e] > 0.5]
graph = nx.Graph()
graph.add_edges_from(selected_edges)
for component in list(nx.connected_components(graph)):
if len(component) < model.inner._n_cities:
cut_edges = tuple(
(e[0], e[1])
for e in model.inner._edges
if (e[0] in component and e[1] not in component)
or (e[0] not in component and e[1] in component)
)
violations.append(cut_edges)
return violations
x_val = model.inner.cbGetSolution(model.inner._x)
return _tsp_separate(x_val, edges, data.n_cities)
def lazy_enforce(model: GurobiModel, violations: List[Any]) -> None:
for violation in violations:
@@ -212,22 +199,9 @@ def build_tsp_model_pyomo(
model.subtour_eqs = pe.ConstraintList()
def lazy_separate(m: PyomoModel) -> List[Any]:
violations = []
m.solver.cbGetSolution([model.x[e] for e in edges])
x_val = {e: model.x[e].value for e in edges}
selected_edges = [e for e in edges if x_val[e] > 0.5]
graph = nx.Graph()
graph.add_edges_from(selected_edges)
for component in list(nx.connected_components(graph)):
if len(component) < data.n_cities:
cut_edges = tuple(
(e[0], e[1])
for e in edges
if (e[0] in component and e[1] not in component)
or (e[0] not in component and e[1] in component)
)
violations.append(cut_edges)
return violations
return _tsp_separate(x_val, edges, data.n_cities)
def lazy_enforce(m: PyomoModel, violations: List[Any]) -> None:
logger.warning(f"Adding {len(violations)} subtour elimination constraints...")
@@ -251,3 +225,24 @@ def _tsp_read(data: Union[str, TravelingSalesmanData]) -> TravelingSalesmanData:
data = read_pkl_gz(data)
assert isinstance(data, TravelingSalesmanData)
return data
def _tsp_separate(
x_val: dict[Tuple[int, int], float],
edges: List[Tuple[int, int]],
n_cities: int,
) -> List[Tuple[Tuple[int, int], ...]]:
violations = []
selected_edges = [e for e in edges if x_val[e] > 0.5]
graph = nx.Graph()
graph.add_edges_from(selected_edges)
for component in list(nx.connected_components(graph)):
if len(component) < n_cities:
cut_edges = tuple(
(e[0], e[1])
for e in edges
if (e[0] in component and e[1] not in component)
or (e[0] not in component and e[1] in component)
)
violations.append(cut_edges)
return violations