gurobipy.GurobiError: Divisor must be a constant

回答済み

Danning Xie

2022年03月07日 16:56

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I was trying to add an objective function to maximize the average probability:

model.setObjectiveN(-sum(x[i,j]*prob[i][j] for i in range(n) for j in range(m))/x.sum(), index=0)

where x is variable defined as:

x = model.addVars(n,m, vtype=GRB.BINARY)

and `prob` is a matrix of size n*m which is previously known data.

 

But I got error

Traceback (most recent call last):
  File "src/gurobipy/linexpr.pxi", line 523, in gurobipy.LinExpr.__truediv__
TypeError: float() argument must be a string or a number, not 'gurobipy.LinExpr'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "constr_solver.py", line 172, in <module>
    main(...)
  File "constr_solver.py", line 137, in main
    x = optimize(...)
  File "constr_solver.py", line 72, in optimize
    model.setObjectiveN(-sum(x[i,j]*prob[i][j] for i in range(n) for j in range(m))/x.sum(), index=0)
  File "src/gurobipy/linexpr.pxi", line 525, in gurobipy.LinExpr.__truediv__
gurobipy.GurobiError: Divisor must be a constant

 

 

 

I want to maximize the average probability for the chosen x.  Is there any other way I can define this? Thank you

 

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  Jaromił Najman

  • Gurobi Staff

  2022年03月08日 10:54 編集済み

  Dividing by a variable (or a sum of variables) is currently not supported in Gurobi. However, with a few auxiliary variables and equality constraints, it is possible to formulate your objective function in Gurobi.

  To formulate a division by an optimization variable, you should introduce an auxiliary variable \(z_n\) for the numerator expression and an auxiliary variable \(z_d\) for the denominator expression, i.e., add equality constraints \(z_n = \text{numerator}\) and \(z_d = \text{denominator}\).
  Next, you can follow the instructions in How do I divide by a variable in Gurobi? to model the division \(\frac{1}{z_d} = x\).
  You can then finally use \(x\) and \(z_n\) in your objective function as \(z_n \cdot x\).
  Please note that your model is nonconvex and you have to set the NonConvex parameter.

  Best regards, 
  Jaromił

   

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  Danning Xie

  2022年03月09日 17:15

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  Thank you! It helps. 

   

   

  Danning

  0

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