def generate_constrs(self, model: Model):
xf, V_, cp, G = model.translate(
self.x), self.V, CutPool(), nx.DiGraph()
for i in xf:
for j in i:
print(j, ' ', end='')
print()
print('V', V_)
print('F', self.F)
for (u, v) in [(k, l) for (k, l) in product(V_, V_)
if k != l and xf[k][l]]:
G.add_edge(u, v, capacity=xf[u][v].x)
print(list(G.nodes(data=True)))
print(list(G.edges))
for (u, v) in F:
val, (S, NS) = nx.minimum_cut(G, u, v)
if val <= 0.99:
aInS = [(xf[i][j], xf[i][j].x) for (i, j) in product(V_, V_)
if i != j and xf[i][j] and i in S and j in S]
if sum(f for v, f in aInS) >= (len(S) - 1) + 1e-4:
cut = xsum(1.0 * v for v, fm in aInS) <= len(S) - 1
cp.add(cut)
if len(cp.cuts) > 256:
for cut in cp.cuts:
model += cut
return
for cut in cp.cuts:
model += cut
def generate_constrs(self, model: Model):
xf, V_, cp, G = model.translate(
self.x), self.V, CutPool(), nx.DiGraph()
# valid edges
for (u, v) in self.graph.edges():
try:
edge = xf[u][v]
G.add_edge(u, v, capacity=xf[u][v].x)
except:
pass
for (u, v) in self.F:
try:
val, (S, NS) = nx.minimum_cut(G, u, v)
if val <= 0.99:
aInS = [(xf[i][j], xf[i][j].x)
for (i, j) in product(V_, V_)
if i != j and xf[i][j] and i in S and j in S]
if sum(f for v, f in aInS) >= (len(S) - 1) + 1e-4:
cut = xsum(1.0 * v for v, fm in aInS) <= len(S) - 1
cp.add(cut)
if len(cp.cuts) > 256:
for cut in cp.cuts:
model += cut
return
except nx.NetworkXError:
pass
for cut in cp.cuts:
model += cut
def generate_constrs(self, model: Model):
x_, N, cp = model.translate(self._x), range(len(self._x)), CutPool()
outa = [[j for j in N if x_[i][j].x >= 0.99] for i in N]
for node in N:
S = set(subtour(N, outa, node))
if S:
AS = [(i, j) for (i, j) in product(S, S) if i != j]
cut = xsum(x_[i][j] for (i, j) in AS) <= len(S) - 1
cp.add(cut)
for cut in cp.cuts:
model += cut
def generate_constrs(self, model: Model):
xf, V_, cp = model.translate(self.x), self.V, CutPool()
for (u, v) in [(k, l) for (k, l) in product(V_, V_) if k != l and xf[k][l]]:
G.add_edge(u, v, capacity=xf[u][v].x)
for (u, v) in F:
val, (S, NS) = nx.minimum_cut(G, u, v)
if val <= 0.99:
aInS = [(xf[i][j], xf[i][j].x)
for (i, j) in product(V_, V_) if i != j and xf[i][j] and i in S and j in S]
if sum(f for v, f in aInS) >= (len(S)-1)+1e-4:
cut = xsum(1.0*v for v, fm in aInS) <= len(S)-1
cp.add(cut)
if len(cp.cuts) > 256:
for cut in cp.cuts:
model += cut
return
for cut in cp.cuts:
model += cut
def generate_constrs(self, m_: Model):
xf, cp, Gl = m_.translate(self.x), CutPool(), nx.DiGraph()
Ar = [(i, j) for (i, j) in Arcs if xf[i][j] and xf[i][j].x >= 1e-4]
for (u, v) in Ar:
Gl.add_edge(u, v, capacity=xf[u][v].x)
for (u, v) in F:
val, (S, NS) = nx.minimum_cut(Gl, u, v)
if val <= 0.99:
aInS = [(xf[i][j], xf[i][j].x) for (i, j) in Ar
if i in S and j in S]
if sum(f for v, f in aInS) >= (len(S) - 1) + 1e-4:
cut = xsum(1.0 * v for v, fm in aInS) <= len(S) - 1
cp.add(cut)
if len(cp.cuts) > 32:
for cut in cp.cuts:
m_ += cut
return
for cut in cp.cuts:
m_ += cut
def generate_constrs(self, model: Model):
xf = model.translate(self.x)
yf = model.translate(self.y)
V_ = range(self.instance.n)
cp = CutPool()
for a in range(self.instance.m):
edges = [[] for i in range(self.instance.n)]
for (u, v) in [
(k, l) for (k, l) in product(V_, range(self.instance.n + 1))
if k != l and abs(yf[k][l][a].x) > 1e-8
]:
print(yf[u][v][a].name, yf[u][v][a].x)
edges[u].append(v)
# print(edges)
# input()
cycles = []
for i in range(self.instance.n):
c = self.cycles(edges[i], i, edges, [i], [])
if c:
for cycle in c:
cycles.append(cycle)
# print('cycles', cycles, 'a ', a)
# input()
for c in cycles:
soma = 0
rhs = len(c) - 1
for i in range(rhs):
u = c[i]
v = c[i + 1]
soma += yf[u][v][a].x
if soma > rhs - 1 + 1e-8:
cut = xsum(self.y[c[i]][c[i + 1]][a]
for i in range(rhs)) <= rhs - 1
# print(cut)
# input()
cp.add(cut)
for cut in cp.cuts:
model += cut
print('Total cuts: {}'.format(len(cp.cuts)))
input()
def generate_constrs(self, model: Model, depth: int = 0, npass: int = 0):
xf, V_, cp, G = model.translate(
self.x), self.V, CutPool(), nx.DiGraph()
for (u, v) in [(k, l) for (k, l) in product(V_, V_)
if k != l and xf[k][l]]:
G.add_edge(u, v, capacity=xf[u][v].x)
for (u, v) in F:
val, (S, NS) = nx.minimum_cut(G, u, v)
if val <= 0.99:
aInS = [(xf[i][j], xf[i][j].x) for (i, j) in product(V_, V_)
if i != j and xf[i][j] and i in S and j in S]
if sum(f for v, f in aInS) >= (len(S) + sum(
[1 if demand[i] > Q else 0 for i in S]) - 1) + 1e-4 + xsum(
[x[g][l] for g in NS for l in S if (g != l)]):
cut = xsum(1.0 * v for v, fm in aInS) <= len(S) - 1 + sum([
1 if demand[i] > Q else 0 for i in S
]) + xsum([x[g][l] for g in NS for l in S if (g != l)])
cp.add(cut)
if len(cp.cuts) > 256:
for cut in cp.cuts:
model += cut
return
for cut in cp.cuts:
model += cut
