Unable to retrieve attribute 'objVal'
Answered
import gurobipy as gp
from gurobipy import GRB
import math
import numpy as np
from matplotlib import pyplot as plt
options = {
"WLSACCESSID": "xxx",
"WLSSECRET": "xxx",
"LICENSEID": xxx,
}
import pandas as pd
import numpy as np
import random
R = np.array([])
for o in range(3,10):
T = np.zeros((o,3))
n = np.zeros(3)
n = np.array([10,15,20])
Totalmaterials = 15
beta_0 = 1
beta_1 = 1
beta_2 = 1
def Traveltime():
random_integer = random.randint(2,4)
return(random_integer)
for i in range(0,o):
for j in range(0,3):
T[i][j]= Traveltime()
def Optimize(n,T,o):
env = gp.Env(params=options)
model = gp.Model(env=env)
z = model.addVars(3, lb = 0, vtype = GRB.CONTINUOUS, name = 'z')
Vi = model.addVars(o, lb = 0, vtype = GRB.CONTINUOUS, name = 'Vi')
qij = model.addMVar((o,3), lb = 0, vtype = GRB.CONTINUOUS, name = 'qij')
Pij = model.addMVar((o,3), vtype = GRB.CONTINUOUS, name = 'Pij')
Qij = model.addMVar((o,3), vtype = GRB.CONTINUOUS, name = 'Qij')
W = model.addMVar((o,3), vtype = GRB.CONTINUOUS, name = 'W')
model.addConstrs(Qij[i,j] == beta_0 - beta_1*T[i,j] + beta_2*Vi[i] for i in range(0,o) for j in range(0,3))
for i in range(0,o):
for j in range(0,3):
model.addGenConstrExp(Qij[i,j], W[i,j], "FuncPieces=-2 FuncPieceError=0.01")
model.addConstrs(Pij[i,j]*sum(W[l,j] for l in range(0,o)) == W[i,j] for i in range(0,o) for j in range(0,3))
model.addConstr(sum(Vi[i] for i in range(0,o)) <= Totalmaterials)
model.addConstrs(Vi[i] == sum(qij[i,j] for j in range(0,3)) for i in range(0,o))
model.addConstrs(qij[i,j] <= n[j]*Pij[i,j] for i in range(0,o) for j in range(0,3))
model.addConstrs(sum(Pij[i,j] for i in range(0,o)) == 1 for j in range(0,3))
model.addConstrs(z[j] == n[j]- sum(qij[i,j] for i in range(0,o)) for j in range(0,3))
obj_fn = gp.quicksum(z[j] for j in range(0,3))
model.setObjective(obj_fn, GRB.MINIMIZE)
model.optimize()
print('Optimization is done. Objective Function Value: %.2f' %model.objVal)
for v in model.getVars():
print('%s: %g' %(v.varName, v.x))
return model.objVal
R = np.append(R,Optimize(n,T,o))
The question is while running the above code for o = 6 it is not able to retrieve attribute 'objVal' and the model is infeasible. But when i solved the problem with another algorithm, I am getting feasible solution for o = 6.
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Did you check the article How do I diagnose a wrong result?
A common issue is that the default lower bound in Gurobi is 0.0 and not -INF as in other solvers.0 -
Thanks Marika Karbstein. It was really helpful insight about the model.
Best,
Dhiraj
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