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_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
