How can I obtain the optimal matching score of each decision variable?
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Hi,
I want to obtain the matching score of each assignment next to the variable. For example, something like that 'assign [Carlos, Tester] Score 53'. When we write "print (v.varName, v.x) it gives the binary variable 1 next to the assignment as in the example. Is there any way to obtain the optimal scores of each decision variable next to the assignment rather than obtaining the binary variable value 1?
Thank you.
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Hi Merve,
That depends on how you are defining and computing those scores. If this is encoded in your constraints, you may want to get the corresponding constraint, get its LinExpr, and call getValue() to get the value of this constraint for the current solution, e.g.:
c = m.getConstrs()[10]
m.getRow(c).getValue()Cheers,
Matthias1 -
It seems, that a[i,j] are your variables. Why don't you just query the X attribute of those variables just like before?
for i in range(num_workers):
for j in range(num_tasks):
if a[i,j].X > 0.5:
print(f'Worker {i} assigned to task {j}. Costs = {costs[i][j]}')Cheers,
Matthias1 -
Hi, actually matching scores (costs) are given in a matrix format as below and scores and the value of the matching is obtained by multiplying the binary variable (1 or 0) and the score as in the objective function in the code. So, it is not encoded in my constraints, so when I try the same way like c=m.getObjective and get.Value to obtain matching scores next to each matching, it did not work. I just want to obtain something like X[0,3] Score 75 , not X[0,3] 1.0 (binary value) as in my output.
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Thank you very much! I could not think about it like that as I am a newbie in Python and Gurobi. Now, I obtained exactly what I wanted thanks to you!
Sincerely,
Merve.
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