print("This feature is currently not supported in Gurobi.")
else:
m.verbose = 0
x = m.add_var_tensor(shape=(2, 1), name="x", var_type=INTEGER)
m.objective = maximize(2 * x[0] + x[1])
m += 7 * x[0] + x[1] <= 28
m += -x[0] + 3 * x[1] <= 7
m += -8 * x[0] - 9 * x[1] <= -32
m.optimize(relax=True)
olr = m.objective_value
cp = m.generate_cuts([ct])
if cp and cp.cuts:
print("{} cuts generated:".format(len(cp.cuts)))
for c in cp.cuts:
print(" " + str(c))
if cp.cuts:
m += cp
m.optimize(relax=True)
print("Dual bound now: {}".format(m.objective_value))
assert m.status == OptimizationStatus.OPTIMAL
diff = m.objective_value - olr
if diff > larger_diff:
larger_diff = diff
best_cut = ct
G = DiGraph()
for a in A:
G.add_edge(a[0], a[1], capacity=x[a].x)
newConstraints = False
for (n1, n2) in [(i, j) for (i, j) in product(N, N) if i != j]:
cut_value, (S, NS) = minimum_cut(G, n1, n2)
if cut_value <= 0.99:
m += (
xsum(x[a] for a in A if (a[0] in S and a[1] in S))
<= len(S) - 1
)
newConstraints = True
if not newConstraints and m.solver_name.lower() == "cbc":
cp = m.generate_cuts(
[
CutType.GOMORY,
CutType.MIR,
CutType.ZERO_HALF,
CutType.KNAPSACK_COVER,
]
)
if cp.cuts:
m += cp
newConstraints = True
# sanity checks
assert m.status == OptimizationStatus.OPTIMAL
assert 260.99 <= m.objective_value <= 262.000001
