What kind of functions can be accepted into Model.setObjective method?

Answered

Vadim Avkhimenia

February 03, 2022 20:45

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Hello,

I have the following code where I am trying to find the value of 'x' for which the function below will be at a minimum:

------------------------------------------------------------------------

from gurobipy import Model, GRB

model = Model()

x = model.addVar(0, float('inf'), name = 'x')

def square_of_x(x):
    if x >= 0:
        return x * x
    else:
        return x

model.setObjective(square_of_x(x), GRB.MINIMIZE)

model.optimize()

------------------------------------------------------------------------

When I run this I get the following error:

GurobiError: Constraint has no bool value (are you trying "lb <= expr <= ub"?)

In a more general problem, I would like to create a function, have the Gurobi variable as an argument in that function, and then minimize the value of that function via an LP optimization, to find the value of the variable that would make the function minimal.

A few questions:

1) Is the 'if statement' the issue in the function? The answer to the optimization should be x = 0.

2) What kinds of functions can Model.setObjective() method accept as an argument?

Thanks. 

0

• Official comment

  

  Simranjit Kaur

  • Gurobi Staff

  November 16, 2025 23:44

  This post is more than three years old. Some information may not be up to date. For current information, please check the Gurobi Documentation or Knowledge Base. If you need more help, please create a new post in the community forum, or try Gurobot, our chatbot interface offering instant, expert-level support.
• 

  Jaromił Najman

  • Gurobi Staff

  February 07, 2022 10:41

  Hi Vadim,

  1) Is the 'if statement' the issue in the function? The answer to the optimization should be x = 0.

  Yes, the if statement is causing the issue. Note that \(x\) is a Var object which does not have any value. You can access the variable solution point value via its X attribute after a solution point is available. In your case, you would have to run optimize first in order to make \(x\) have a solution point value available.

  In Mathemtical Programming, you can model \(\texttt{if}\)-statements via additional binary variables and constraints, cf. How do I model conditional statements in Gurobi? In your case, it is much easier. You can just set the objective function to \(x^2\) via

  model.setObjective(x*x, GRB.MINIMIZE)

  2) What kinds of functions can Model.setObjective() method accept as an argument?

  According to the documentation of the setObjective method, it accepts linear and quadratic expressions.

  Best regards, 
  Jaromił

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