Improve performance of constraint-adding in Gurobi Python
OngoingIn the model I am working on I have to add constraints, the constraints based on the edges of a graph, I have the decision variable
x = {}
for (i, j) in E:
x[i, j] = model.addVar(vtype=GRB.BINARY, name="x%d,%d," % (i, j))
then I have to constraints, for instance :
# Constraint 1
model.addConstrs((x[i, j] + x[j, i] <= 1 for (i, j) in E), name='first')
# Constraint 4
model.addConstrs(((quicksum(x[g, i] for g in range(initial, n + 1) if (g, i) in E and g != i and g != j)
+ quicksum(x[j, g] for g in range(initial, n + 1) if (j, g) in E and g != j and g != i)
) <= 2 for (i, j) in E)
, name='fourth')
now E is defined in this way :
E = gp.tuplelist([(0, 1), (5, 22), (15, 27), (29, 33), (9, 3), (29, 12), (29, 22), (8, 39),
(0, 2), (6, 14), (16, 19), (29, 34), (11, 3), (32, 12), (31, 22), (39, 8),
(0, 3), (6, 27), (16, 22), (29, 36), (12, 3), (15, 13), (33, 22), (9, 39),
(0, 9), (7, 9), (16, 24), (29, 37), (15, 3), (17, 13), (36, 22), (39, 9),
(0, 11), (7, 11), (16, 26), (30, 32), (22, 3), (22, 13), (37, 22), (10, 39)])
my problem is when E with a lot of edges it takes a lot of time to create the constraints, there is any way to add variables and constraints in a more efficient way?
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Hi,
The time issue is not reproducible. The value of the \(\texttt{initial}\) parameter is missing. Constraint 1 results in a Keyerror because \(\texttt{x[1,0]}\) is not present. Could you provide a minimal reproducible example (MRE) showing the build time issue?
Best regards,
Jaromił0 -
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Hi Jaromil, this is just the smallest example I have, the time here is acceptable but when the graph has hundreds or thousands of nodes and edges it really takes a lot of time, there is any part that can be modified to avoid this?
Thanks alot
import gurobipy as gp
from gurobipy import GRB, quicksum
from collections import defaultdict
#############################################
initial = 0
n = 39
s = 39
E = gp.tuplelist([(0, 1), (6, 32), (14, 15), (28, 31), (30, 4), (32, 11), (31, 20), (39, 15),
(0, 12), (6, 33), (14, 16), (28, 32), (9, 5), (33, 11), (32, 20), (16, 39),
(0, 22), (6, 35), (14, 17), (28, 33), (11, 5), (34, 11), (34, 20), (39, 16),
(0, 2), (6, 36), (14, 18), (28, 34), (12, 5), (35, 11), (35, 20), (17, 39),
(0, 13), (6, 37), (14, 19), (28, 35), (14, 5), (36, 11), (23, 22), (39, 17),
(0, 3), (6, 38), (14, 20), (28, 36), (28, 5), (37, 11), (28, 25), (18, 39),
(0, 4), (7, 9), (14, 21), (28, 37), (9, 6), (38, 11), (28, 26), (39, 18),
(0, 5), (7, 11), (14, 24), (28, 38), (11, 6), (13, 12), (36, 26), (19, 39),
(0, 9), (7, 12), (14, 25), (29, 36), (12, 6), (14, 12), (28, 27), (39, 19),
(0, 11), (7, 14), (14, 26), (32, 37), (14, 6), (14, 13), (29, 28), (20, 39),
(1, 2), (7, 28), (14, 27), (35, 38), (28, 6), (24, 13), (30, 28), (39, 20),
(1, 3), (7, 35), (14, 29), (1, 0), (32, 6), (15, 14), (31, 28), (21, 39),
(1, 4), (7, 36), (14, 30), (12, 0), (33, 6), (16, 14), (32, 28), (39, 21),
(1, 5), (7, 37), (14, 31), (22, 0), (35, 6), (17, 14), (33, 28), (22, 39),
(1, 6), (8, 10), (14, 32), (2, 0), (36, 6), (18, 14), (34, 28), (39, 22),
(1, 7), (8, 23), (14, 33), (13, 0), (37, 6), (19, 14), (35, 28), (23, 39),
(1, 8), (9, 10), (14, 34), (3, 0), (38, 6), (20, 14), (36, 28), (39, 23),
(1, 9), (9, 12), (14, 35), (4, 0), (9, 7), (21, 14), (37, 28), (24, 39),
(1, 10), (9, 13), (14, 36), (5, 0), (11, 7), (24, 14), (38, 28), (39, 24),
(1, 11), (9, 14), (14, 37), (9, 0), (12, 7), (25, 14), (36, 29), (25, 39),
(2, 6), (9, 22), (14, 38), (11, 0), (14, 7), (26, 14), (37, 32), (39, 25),
(2, 7), (9, 23), (15, 16), (2, 1), (28, 7), (27, 14), (38, 35), (26, 39),
(2, 9), (9, 24), (15, 30), (3, 1), (35, 7), (29, 14), (0, 39), (39, 26),
(2, 11), (10, 21), (15, 31), (4, 1), (36, 7), (30, 14), (39, 0), (27, 39),
(2, 12), (11, 12), (15, 32), (5, 1), (37, 7), (31, 14), (1, 39), (39, 27),
(2, 13), (11, 13), (15, 33), (6, 1), (10, 8), (32, 14), (39, 1), (28, 39),
(2, 24), (11, 15), (15, 34), (7, 1), (23, 8), (33, 14), (2, 39), (39, 28),
(2, 25), (11, 16), (16, 17), (8, 1), (10, 9), (34, 14), (39, 2), (29, 39),
(2, 26), (11, 17), (16, 18), (9, 1), (12, 9), (35, 14), (3, 39), (39, 29),
(2, 27), (11, 18), (16, 19), (10, 1), (13, 9), (36, 14), (39, 3), (30, 39),
(2, 28), (11, 19), (16, 20), (11, 1), (14, 9), (37, 14), (4, 39), (39, 30),
(3, 9), (11, 20), (17, 29), (6, 2), (22, 9), (38, 14), (39, 4), (31, 39),
(3, 11), (11, 21), (17, 30), (7, 2), (23, 9), (16, 15), (5, 39), (39, 31),
(3, 12), (11, 22), (17, 31), (9, 2), (24, 9), (30, 15), (39, 5), (32, 39),
(3, 14), (11, 23), (17, 32), (11, 2), (21, 10), (31, 15), (6, 39), (39, 32),
(3, 29), (11, 24), (17, 33), (12, 2), (12, 11), (32, 15), (39, 6), (33, 39),
(4, 9), (11, 25), (17, 34), (13, 2), (13, 11), (33, 15), (7, 39), (39, 33),
(4, 11), (11, 26), (18, 29), (24, 2), (15, 11), (34, 15), (39, 7), (34, 39),
(4, 12), (11, 27), (18, 32), (25, 2), (16, 11), (17, 16), (8, 39), (39, 34),
(4, 14), (11, 29), (19, 21), (26, 2), (17, 11), (18, 16), (39, 8), (35, 39),
(4, 28), (11, 30), (20, 29), (27, 2), (18, 11), (19, 16), (9, 39), (39, 35),
(4, 29), (11, 31), (20, 30), (28, 2), (19, 11), (20, 16), (39, 9), (36, 39),
(4, 30), (11, 32), (20, 31), (9, 3), (20, 11), (29, 17), (10, 39), (39, 36),
(5, 9), (11, 33), (20, 32), (11, 3), (21, 11), (30, 17), (39, 10), (37, 39),
(5, 11), (11, 34), (20, 34), (12, 3), (22, 11), (31, 17), (11, 39), (39, 37),
(5, 12), (11, 35), (20, 35), (14, 3), (23, 11), (32, 17), (39, 11), (38, 39),
(5, 14), (11, 36), (22, 23), (29, 3), (24, 11), (33, 17), (12, 39), (39, 38),
(5, 28), (11, 37), (25, 28), (9, 4), (25, 11), (34, 17), (39, 12),
(6, 9), (11, 38), (26, 28), (11, 4), (26, 11), (29, 18), (13, 39),
(6, 11), (12, 13), (26, 36), (12, 4), (27, 11), (32, 18), (39, 13),
(6, 12), (12, 14), (27, 28), (14, 4), (29, 11), (21, 19), (14, 39),
(6, 14), (13, 14), (28, 29), (28, 4), (30, 11), (29, 20), (39, 14),
(6, 28), (13, 24), (28, 30), (29, 4), (31, 11), (30, 20), (15, 39)])
E = sorted(E)
#######################################################
try:
with gp.Model("sub_problem") as model:
y = {}
u = {}
for a in range(initial, n):
y[a] = model.addVar(lb=0, name="y%d" % a)
for b in range(initial, n + 1):
u[b] = model.addVar(lb=0, name="u%d" % b)
for (i, j) in E:
xH = defaultdict(lambda: 0, {(i, j): 0, })
xH[1, 0] = 1
xH[0, 39] = 1
xH[39, 1] = 1
# Constraint 1,2
for (i, j) in E:
if i != s and j != s:
model.addLConstr(y[i] >= xH[i, j], name='first%d,%d' % (i, j))
model.addLConstr(y[j] >= xH[i, j], name='second%d,%d' % (i, j))
# Constraint 3,4
for i in range(initial, n):
model.addLConstr(y[i] == quicksum(xH[i, j] for j in range(initial, n + 1) if (i, j) in E),
name='third%d' % i)
model.addLConstr(y[i] == quicksum(xH[j, i] for j in range(initial, n + 1) if (j, i) in E),
name='fourth%d' % i)
# Constraint 5
for (i, j) in E:
if j != s:
model.addLConstr(u[i] - u[j] <= (n * (1 - xH[i, j]) - 1), name='fifth%d,%d' % (i, j))
# Constraint 6
model.addLConstr(u[s] == 1, name='sixth')
# Set global sense for ALL objectives
model.ModelSense = GRB.MINIMIZE
# Set objective
model.setObjective(-1 * (quicksum(y[i] for i in range(initial, n))))
# Save model
model.write('SP2.lp')
finally:
gp.disposeDefaultEnv()
try:
with gp.Model("master_problem") as model:
Z = model.addVar(lb=-gp.GRB.INFINITY, name="Z")
x = {}
for (i, j) in E:
x[i, j] = model.addVar(vtype=GRB.BINARY, name="x%d,%d," % (i, j))
# Constraint 1
for (i, j) in E:
model.addLConstr(x[i, j] + x[j, i] <= 1, name='first%d,%d' % (i, j))
# Constraint 2
model.addLConstr(quicksum(x[s, v] for v in range(initial, n)) == 1, name='second')
# Constraint 3
model.addLConstr(quicksum(x[v, s] for v in range(initial, n)) == 1, name='third')
# Constraint 4
for (i, j) in E:
if i != s and j != s:
model.addLConstr(
(quicksum(x[g, i] for g in range(initial, n + 1) if (g, i) in E and g != i and g != j)
+quicksum(x[i, g] for g in range(initial, n + 1) if (i, g) in E and g != i and g != j)
+ quicksum(x[j, g] for g in range(initial, n + 1) if (j, g) in E and g != j and g != i)
+ quicksum(x[g, j] for g in range(initial, n + 1) if (g, j) in E and g != i and g != j))
<= 2
, name='fourth%d,%d' % (i, j))
# Constraint 5,6,7
for i in range(initial, n):
model.addLConstr((quicksum(x[i, j] for j in range(initial, n + 1) if (i, j) in E and i < j) <= 1),
name='fifth%d' % i)
model.addLConstr((quicksum(x[j, i] for j in range(initial, n + 1) if (j, i) in E and i < j) <= 1),
name='sixth%d' % i)
model.addLConstr((quicksum(x[j, i] for j in range(initial, n + 1) if (j, i) in E)) ==
(quicksum(x[i, j] for j in range(initial, n + 1) if (i, j) in E)), name='seventh%d' % i)
# Set global sense for ALL objectives
model.ModelSense = GRB.MINIMIZE
# Set objective
model.setObjective(Z)
# Save model
model.write('MP2.lp')
finally:
gp.disposeDefaultEnv()
########################################################
for (i, j) in E:
if i != s and j != s:
d = defaultdict(lambda: 0.0, {(1, i, j): 0.0, })
f = defaultdict(lambda: 0.0, {(1, i, j): 0.0, })
for v in range(initial, n):
p = defaultdict(lambda: 0.0, {(1, v): 0.0, })
m = defaultdict(lambda: 0.0, {(1, v): 0.0, })
for (i, j) in E:
if j != s:
l = defaultdict(lambda: 0.0, {(1, i, j): 0.0, })
t = defaultdict(lambda: 0.0, {1: 0.0, })
###################################################
SP_model2 = gp.read("SP2.lp")
MP_model2 = gp.read("MP2.lp")
SP_model2.setParam(GRB.Param.Presolve, 0)
SP_model2.setParam("InfUnbdInfo", 1)
SP_model2.optimize()
#####################################################
x_temp = MP_model2.getVars()
Z = x_temp[0]
x_temp.pop(0)
variables = sorted(x_temp, key=lambda x: (float(x.VarName.split(",")[0][1:]), float(x.VarName.split(",")[1])))
#######################################################
init = 0
for (a, b) in E:
x[a, b] = variables[init]
init += 1
##################################################
# k = 0
if SP_model2.status >= 3:
k = 1
for (i, j) in E:
if i != s and j != s:
d[k, i, j] = -1 * SP_model2.getConstrByName('first%d,%d' % (i, j)).FarkasDual
f[k, i, j] = -1 * SP_model2.getConstrByName('second%d,%d' % (i, j)).FarkasDual
for v in range(initial, n):
p[k, v] = -1 * SP_model2.getConstrByName('third%d' % v).FarkasDual
m[k, v] = -1 * SP_model2.getConstrByName('fourth%d' % v).FarkasDual
for (i, j) in E:
if j != s:
l[k, i, j] = -1 * SP_model2.getConstrByName('fifth%d,%d' % (i, j)).FarkasDual
t[k] = -1 * SP_model2.getConstrByName('sixth').FarkasDual
MP_model2.addConstr(0 >= (quicksum(x[i, j] * d[k, i, j] for (i, j) in E if i != s and j != s)
+ quicksum(x[i, j] * f[k, i, j] for (i, j) in E if i != s and j != s)
+ quicksum(x[i, j] * p[k, i] for (i, j) in E if i != s)
+ quicksum(x[j, i] * m[k, i] for (j, i) in E if i != s)
+ quicksum((n * (1 - x[i, j]) - 1) * l[k, i, j] for (i, j) in E if j != s)
+ t[k]), name='cut%d' % k)
MP_model2.write("MP2.lp")
else:
k = 1
for (i, j) in E:
if i != s and j != s:
d[k, i, j] = SP_model2.getConstrByName('first%d,%d' % (i, j)).Pi
f[k, i, j] = SP_model2.getConstrByName('second%d,%d' % (i, j)).Pi
for v in range(initial, n):
p[k, v] = SP_model2.getConstrByName('third%d' % v).Pi
m[k, v] = SP_model2.getConstrByName('fourth%d' % v).Pi
for (i, j) in E:
if j != s:
l[k, i, j] = SP_model2.getConstrByName('fifth%d,%d' % (i, j)).Pi
t[k] = SP_model2.getConstrByName('sixth').Pi
MP_model2.addConstr((quicksum(x[i, j] * d[k, i, j] for (i, j) in E if i != s and j != s)
+ quicksum(x[i, j] * f[k, i, j] for (i, j) in E if i != s and j != s)
+ quicksum(x[i, j] * p[k, i] for (i, j) in E if i != s)
+ quicksum(x[j, i] * m[k, i] for (j, i) in E if i != s)
+ quicksum((n * (1 - x[i, j]) - 1) * l[k, i, j] for (i, j) in E if j != s)
+ t[k]) <= Z, name='cut%d' % k)
MP_model2.write("MP2.lp")
MP_model2.setParam(GRB.Param.Presolve, 0)
MP_model2.optimize()
print("####################################")
print('The optimal objective SP is %g' % SP_model2.objVal)
print('The optimal objective MP is %g' % MP_model2.objVal)
print("####################################")
for (st, nd) in E:
if nd != s:
fifth = SP_model2.getConstrByName('fifth%d,%d' % (st, nd))
fifth.rhs = n * (1 - x[st, nd].X) - 1
for (st2, nd2) in E:
if st2 != s and nd2 != s:
first = SP_model2.getConstrByName('first%d,%d' % (st2, nd2))
second = SP_model2.getConstrByName('second%d,%d' % (st2, nd2))
first.rhs = x[st2, nd2].X
second.rhs = x[st2, nd2].X
for st3 in range(initial, n):
third = SP_model2.getConstrByName('third%d' % st3)
fourth = SP_model2.getConstrByName('fourth%d' % st3)
temp_x1 = 0
for nd3 in range(initial, n + 1):
if (st3, nd3) in E:
temp_x1 += x[st3, nd3].X
third.rhs = temp_x1
fourth.rhs = temp_x1
SP_model2.write("SP2.lp")
###########################################################0 -
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