def generate_constrs(self, model: Model):
G = nx.DiGraph()
r = [(v, v.x) for v in model.vars if v.name.startswith("x(")]
U = [v.name.split("(")[1].split(",")[0] for v, f in r]
V = [v.name.split(")")[0].split(",")[1] for v, f in r]
N = list(set(U + V))
cp = CutPool()
for i in range(len(U)):
G.add_edge(U[i], V[i], capacity=r[i][1])
for (u, v) in product(N, N):
if u == v:
continue
val, (S, NS) = nx.minimum_cut(G, u, v)
if val <= 0.99:
arcsInS = [(v, f) for i, (v, f) in enumerate(r)
if U[i] in S and V[i] in S]
if sum(f for v, f in arcsInS) >= (len(S) - 1) + 1e-4:
cut = xsum(1.0 * v for v, fm in arcsInS) <= len(S) - 1
cp.add(cut)
if len(cp.cuts) > 256:
for cut in cp.cuts:
model.add_cut(cut)
return
for cut in cp.cuts:
model.add_cut(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):
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):
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, 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
def generate_cuts(self, model: Model):
self.x = [[(0, 0) for i in range(self.instance.m)]
for j in range(self.instance.n)]
self.y = [[[(0, 0) for i in range(self.instance.m)]
for k in range(self.instance.n)]
for j in range(self.instance.n)]
# recreate the set of vars used in the model. if position 1 have value = 0 and not a var object
# the variable isn't used in the model
for v in model.vars:
if v.name.startswith('C'):
self.c = (v, v.x)
if v.name.startswith('x('):
j = int(v.name.split('(')[1].split(',')[0])
i = int(v.name.split(')')[0].split(',')[1])
self.x[j][i] = (v, v.x)
if v.name.startswith('y('):
j = int(v.name.split('(')[1].split(',')[0])
k = int(v.name.split('(')[1].split(',')[1])
i = int(v.name.split(')')[0].split(',')[2])
self.y[j][k][i] = (v, v.x)
# print('{} = {}'.format(self.c[0].name, self.c[1]))
# for j in range(self.instance.n):
# for i in range(self.instance.m):
# if isinstance(self.x[j][i][0], int) == False:
# print('{} = {}'.format(self.x[j][i][0].name, self.x[j][i][1]))
# for j in range(self.instance.n):
# for k in range(self.instance.n):
# for i in range(self.instance.m):
# if isinstance(self.y[j][k][i][0], int) == False:
# print('{} = {}'.format(self.y[j][k][i][0].name, self.y[j][k][i][1]))
#
# input()
cp = CutPool()
for a in range(self.instance.m):
# all possible combinations with 2 jobs. order doesnt' matter
# comb = combinations(list(range(0, self.instance.n)), 2)
# for jobs in list(comb):
# result = self.two_jobs_cuts(jobs[0], jobs[1], a)
# if isinstance(result, int) == False:
# # print(result)
# cp.add(result)
# all possible combinations with 3 josb. the order matters
# perm = permutations(list(range(0, self.instance.n)), 3)
# for jobs in list(perm):
# result = self.triangle_cuts(jobs[0], jobs[1], jobs[2], a)
# if isinstance(result, int) == False:
# # print(result)
# cp.add(result)
result = self.basic_cuts_best(a)
if isinstance(result, int) == False:
# print(result)
cp.add(result)
result = self.triangle_cuts_best(a)
if isinstance(result, int) == False:
# print(result)
cp.add(result)
result = self.two_jobs_cuts_best(a)
if isinstance(result, int) == False:
# print(result)
cp.add(result)
for k in range(self.instance.n):
result = self.basic_cuts_plus_epsilon_best(a, k)
if isinstance(result, int) == False:
# print(result)
cp.add(result)
result = self.half_cuts_best(a, k)
if isinstance(result, int) == False:
# print(result)
cp.add(result)
for l in range(self.instance.n):
result = self.late_job_cuts_best(a, k, l)
if isinstance(result, int) == False:
# print(result)
cp.add(result)
# i = 0
for cut in cp.cuts:
# i = i + 1
model.add_cut(cut)
# print('Number of cuts: {}'.format(i))
return
