Possible to define objective parameters in constraints?
AnsweredHi, I have a problem defining some parameters that I want to use in my objective function. I want to define the parameter used in the objective function in the constraints, but it only returns that the parameter u is not defined. An example of what i want to do:
max u11*x1 + u12*x2 + u21*x1 + u22*x2
subject to:
u[i,j] = ....
+ more constraints
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Official comment
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Gurobi Staff
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Community Moderator
Hi Tiril!
Could you share a minimal reproducible example of the code which throws the error? We will then be able to give you better advice.
Best regards
Jonasz0 -
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import pandas as pd
import gurobipy as gp
from gurobipy import *
import numpy as np
from gurobipy import GRB
import matplotlib.pyplot as plt
import sys
## Sets ##
criteria = [0, 1, 2, 3, 4]
decisionM = [0, 1]
alternative = [0, 1]
## Parameters ##
weight = np.array( [[0.03, 0.09, 0.28, 0.14, 0.46], [0.39, 0.15, 0.08, 0.06, 0.32]])
V1 = np.array([[59800000, 68, 0.5, 0.5, 40], [65622000, 165, 0.58, 0.5, 76]])
V2 = np.array([[59800000, 68, 1, 1, 1100], [65622000, 165, 0.75, 0.5, 450]])
V1_min = []
for c in criteria:
if V1[0,c]<V1[1,c]:
V1_min.append(V1[0,c])
else:
V1_min.append(V1[1,c])
V2_min = []
for c in criteria:
if V2[0,c]<V2[1,c]:
V2_min.append(V1[0,c])
else:
V2_min.append(V2[1,c])
## Model ##
m = gp.Model('Weighted-sum-method')
#Decision variable
x = m.addVars(alternative, decisionM, vtype=GRB.BINARY, name='x')
# Defining U1
for c in criteria:
for a in alternative:
m.addConstr(
(U1[a,c] == V1_min[c]/V1[a,c]), 'Utility1')
# Defining U2
for c in criteria:
for a in alternative:
m.addConstr(
(U2[a,c] == V2_min[c]/V2[a,c]), 'Utility1')
# Only one alternative can be chosen by each decision maker
for a in alternative:
m.addConstr(
(sum(x[a,d] for d in decisionM) == 1), 'onealternative')
# Objective function
obj = m.setObjective(sum(x[a,0]*weight[0,c]*U1[a,c] for a in alternative
for c in criteria) + sum(x[a,1]*weight[1,c]*U2[a,c]
for a in alternative for c in criteria),
GRB.MAXIMIZE)
m.optimize()0 -
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Hi Tiril,
1. What are \(U1, U2\)? Are they variables? If so, you need to define them as such upfront, for example by:
U1 = m.addVars(alternative, criteria, vtype="C", name="u1")
U2 = m.addVars(alternative, criteria, vtype="C", name="u2")just after the model definition. Adding these lines solved the problem on my machine.
2. On a side note, you may want to give all constraints different names. Your code names both U1 and U2 constraints 'Utility1'.
Best regards
Jonasz0 -
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Thank you, it worked!
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