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This commit is contained in:
Alinson S. Xavier
2022-06-01 11:40:48 -05:00
parent 3fd252659e
commit 6cc253a903
15 changed files with 591 additions and 275 deletions
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32
miplearn/problems/knapsack.py
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@@ -57,8 +57,8 @@ class MultiKnapsackInstance(Instance):
model = pe.ConcreteModel()
model.x = pe.Var(range(self.n), domain=pe.Binary)
model.OBJ = pe.Objective(
expr=sum(model.x[j] * self.prices[j] for j in range(self.n)),
sense=pe.maximize,
expr=sum(-model.x[j] * self.prices[j] for j in range(self.n)),
sense=pe.minimize,
)
model.eq_capacity = pe.ConstraintList()
for i in range(self.m):
@@ -82,6 +82,7 @@ class MultiKnapsackGenerator:
alpha: rv_frozen = uniform(loc=0.25, scale=0.0),
fix_w: bool = False,
w_jitter: rv_frozen = uniform(loc=1.0, scale=0.0),
p_jitter: rv_frozen = uniform(loc=1.0, scale=0.0),
round: bool = True,
):
"""Initialize the problem generator.
@@ -165,6 +166,7 @@ class MultiKnapsackGenerator:
self.K = K
self.alpha = alpha
self.w_jitter = w_jitter
self.p_jitter = p_jitter
self.round = round
self.fix_n: Optional[int] = None
self.fix_m: Optional[int] = None
@@ -179,8 +181,8 @@ class MultiKnapsackGenerator:
self.fix_u = self.u.rvs(self.fix_n)
self.fix_K = self.K.rvs()
def generate(self, n_samples: int) -> List[MultiKnapsackInstance]:
def _sample() -> MultiKnapsackInstance:
def generate(self, n_samples: int) -> List[MultiKnapsackData]:
def _sample() -> MultiKnapsackData:
if self.fix_w is not None:
assert self.fix_m is not None
assert self.fix_n is not None
@@ -199,12 +201,30 @@ class MultiKnapsackGenerator:
K = self.K.rvs()
w = w * np.array([self.w_jitter.rvs(n) for _ in range(m)])
alpha = self.alpha.rvs(m)
p = np.array([w[:, j].sum() / m + K * u[j] for j in range(n)])
p = np.array(
[w[:, j].sum() / m + K * u[j] for j in range(n)]
) * self.p_jitter.rvs(n)
b = np.array([w[i, :].sum() * alpha[i] for i in range(m)])
if self.round:
p = p.round()
b = b.round()
w = w.round()
return MultiKnapsackInstance(p, b, w)
return MultiKnapsackData(p, b, w)
return [_sample() for _ in range(n_samples)]
def build_multiknapsack_model(data: MultiKnapsackData) -> pe.ConcreteModel:
model = pe.ConcreteModel()
m, n = data.weights.shape
model.x = pe.Var(range(n), domain=pe.Binary)
model.OBJ = pe.Objective(
expr=sum(-model.x[j] * data.prices[j] for j in range(n)),
sense=pe.minimize,
)
model.eq_capacity = pe.ConstraintList()
for i in range(m):
model.eq_capacity.add(
sum(model.x[j] * data.weights[i, j] for j in range(n)) <= data.capacities[i]
)
return model

4
miplearn/problems/stab.py
View File

@@ -114,8 +114,8 @@ def build_stab_model(data: MaxWeightStableSetData) -> pe.ConcreteModel:
nodes = list(data.graph.nodes)
model.x = pe.Var(nodes, domain=pe.Binary)
model.OBJ = pe.Objective(
expr=sum(model.x[v] * data.weights[v] for v in nodes),
sense=pe.maximize,
expr=sum(-model.x[v] * data.weights[v] for v in nodes),
sense=pe.minimize,
)
model.clique_eqs = pe.ConstraintList()
for clique in nx.find_cliques(data.graph):