How to round up in gurobi python?

I am working on a math. model and I use python to solve it.

I have 4 sets

1. Trucks=[1:263]
2. Slots=[0:23]
3. Companies=[0:3]
4. Blocks=[0:7]

And two binary decision variables X and Y
and one binary dependent decision variable Z (Z=X+Y).
I want to add the continuous-time parameters (tp+twg) to the index s (which is an integer) to make the truck access the terminal in the time slot after (tp+twg). So I have to round the value of (s+tp+twg) to the next time slot. I used the function below math.ceil() but I got an error in time slot 23. Gurobi can't calculate the value of (0,0,1,24) because the upper limit of the set S is 23. S refers to the time slot at which the truck will access the terminal in X and Y. In Z, it refers to the time slot at which the truck will arrive at the terminal gate. How can I fix that?

for i in Trucks:
    for k in Companies:
        for b in Blocks:
            for s in Slots:
                if 0 <= s < 23:
                    cont_9=m.addConstr(X[i,k,b, math.ceil(s+tp[s]+twg[s])]+Y[i,k,b, math.ceil(s+tp[s]+twg[s])] <= Z[i,k,b,s])

Jaromił Najman

Gurobi Staff

September 07, 2020 14:19
Edited

Hi,

What values can your continuous-time parameters take? Is it possible that \(\texttt{tp[s]+twg[s]}\geq 2\) for some \(s\)? If yes, then you have to somehow limit \(s\) even further to, e.g., \(\texttt{0 <= s <= 20}\).

A different approach would be to compute the value of \(\texttt{math.ceil(s+p[s]+twg[s])}\) before adding the constraint and then adjust it appropriately such that it fits within the slot bounds.

Best regards,
Jaromił

September 08, 2020 09:29

This is a cross-post from https://stackoverflow.com/questions/63775312/how-to-round-up-in-gurobi-python

How to round up in gurobi python?

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