Use value of Var as dictionary key

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Huib Meulenbelt

• 2021年09月06日 14:08
• 編集済み

Hi all,

I have the following Var and corresponding constraints:

m = gurobi.Model()

s_vars = m.addVars(4, lb=0, ub=5, vtype=gurobi.GRB.CONTINUOUS, name='s')
m.update()

m.addConstr(s_vars[0] == 2)
m.addConstr(s_vars[1] == 2)
m.addConstr(s_vars[2] == 0)
m.addConstr(s_vars[3] == 3)

m.optimize()

In addition, I have a dictionary:

optimal_values = defaultdict(int)
optimal_values[0] = 0
optimal_values[1] = 10
optimal_values[2] = 100
optimal_values[3] = 1000

If I run 

gurobi.quicksum([optimal_values[s_var] for s_var in s_vars])

the output is 

<gurobi.LinExpr: 11100.0>

I expected this to be 12000

Running 

gurobi.quicksum([optimal_values[s_var.Xn] for s_var in s_vars.values()])

shows 

<gurobi.LinExpr: 12000.0>

Although the second option gives the right output, I am note sure whether this is the appropriate methodology. Maybe I am mistaken, but I haven't seen any other code that uses Xn in quicksum. Please advice

1

• 正式なコメント

  

  Simranjit Kaur

  Gurobi Staff

  • 2024年12月06日 00:26

  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 why not try our AI Gurobot?.
• 

  Jaromił Najman

  Gurobi Staff

  • 2021年09月06日 15:34
  • 編集済み

  Hi,

  The addVars function returns a tupledict. As a consequence, the values of \(\texttt{s_var}\) in the

  for s_var in s_vars

  loop return the keys to the variables, i.e., values \(0-3\). Thus, the \(\texttt{quicksum}\)

  gp.quicksum([optimal_values[s_var] for s_var in s_vars])

  returns the sum over

  optimal_values[0], optimal_values[1], optimal_values[2], optimal_values[3]

  However, the second quicksum

  gp.quicksum([optimal_values[s_var.X] for s_var in s_vars.values()])

  actually accesses the variable objects because you loop over the variable objects as you use \(\texttt{s_vars.values()}\). This then sums the values

  optimal_values[s_var[0].X], optimal_values[s_var[1].X], optimal_values[s_var[2].X], optimal_values[s_var[3].X]

  This is the same as

  gp.quicksum([optimal_values[s_vars[s_var].X] for s_var in s_vars])

  This is OK as long as you can ensure that the variable solution values are integer and within the \(0-3\) range.

  Best regards,
  Jaromił

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