CODEWITHSUNDEEP
python-3.xgurobi
magladde
magladde

Reputation: 634

Gurobi using the obj parameter from addVar

I am new to gurobi and I do not understand why the following two code snippets do not return the same minimized objective function. I am attempting to set the objective function coefficient from the addVar function instead of the setObjective function.

Code Snippet 1:

import gurobipy as gb
from gurobipy import GRB

# create model
m = gb.Model()

# add variables
b = m.addVar(vtype=GRB.CONTINUOUS, lb=0, ub=1500000, name="variable_1")
c = m.addVar(vtype=GRB.CONTINUOUS, lb=0, ub=1200000, name="variable_2")
p = m.addVar(vtype=GRB.CONTINUOUS, lb=0, ub=2000000, name="variable_3")


# add objective function
m.setObjective(.5 * b + .6 * c + .7 * p, GRB.MINIMIZE)


# add constraints
m.addConstr(b + c + p == 4000000, "constraint_one")
m.addConstr(-3 * b - 18 * c + 7 * p >= 0, "constraint_two")
m.addConstr(-b + 4 * c + 2 * p >= 0, "constraint_three")

m.optimize()

Code Snippet 2:

import gurobipy as gb
from gurobipy import GRB

# create model
m = gb.Model()

# add variables
b = m.addVar(vtype=GRB.CONTINUOUS, lb=0, obj=0.5, ub=1500000, name="variable_1")
c = m.addVar(vtype=GRB.CONTINUOUS, lb=0, obj=0.6, ub=1200000, name="variable_2")
p = m.addVar(vtype=GRB.CONTINUOUS, lb=0, obj=0.7, ub=2000000, name="variable_3")


# add objective function
m.setObjective(b + c + p, GRB.MINIMIZE)


# add constraints
m.addConstr(b + c + p == 4000000, "constraint_one")
m.addConstr(-3 * b - 18 * c + 7 * p >= 0, "constraint_two")
m.addConstr(-b + 4 * c + 2 * p >= 0, "constraint_three")

m.optimize()

Upvotes: 1

Views: 1918

Answers (1)

Greg Glockner
Greg Glockner

Reputation: 5653

Use Model.setObjective() for code like snippet 1, when you want to specify the objective using a linear expression (LinExpr object). For snippet 2, you already specified the objective coefficients when you called Model.addVar(); instead, call m.ModelSense = GRB.MINIMIZE to tell Gurobi that you want to minimize the objective function.

Upvotes: 2

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