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I am fairly new to linear programming since I came across this topic at university this semester. We mainly focus on nurse rostering. In the lecture, we created a very basic rostering model with an objective function and two constraints. Nr. 1 is the demand constraint and nr.2 is the individual working constraint. I now want to build upon this model and add a few constraints.

In our model, we have two binary variables: $a_{its}$ indicates if nurse $i$ works the shift $s$ on day $t$. $b_{it}$ indicates if nurse $i$ works on day $t$. The index goes from $i;t;s \in \{1,\dots,I;T;S\}$. I now want to model the following:

  1. A nurse must work at least $E_\min$ days at a stretch. To avoid off-on-off patterns so to speak.
  2. A nurse may work a maximum of $E_\max$ days at a stretch. My suggestion would be: $\sum_{j=t}^{j+E_\max}b_{ij}\le E_\max~\forall i\in I, t\in \{1,\dots,|T| -E_\max\}$
  3. A break between work sequences must always be exactly 2 days.

How do I model those linear constraints?

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    $\begingroup$ For the first and second, it seems you would need to limit the LB and UB of the constraints with your predefined parameters. E.g. $\{\sum_{s,t} x_{i,s,t} = u_{i}, \quad \forall i \}$, $ \{E_{min} \leq u_{i} \leq E_{max}, \quad \forall i \}$. And for the third the conditional expression $\{(y_{i,t} \land y_{i,t+1}) \implies (\lnot y_{i,t+2}), \quad \forall i,t \}$. I hope it helps. $\endgroup$
    – A.Omidi
    Commented May 31, 2023 at 13:06
  • $\begingroup$ or.stackexchange.com/questions/9819/… $\endgroup$
    – RobPratt
    Commented May 31, 2023 at 13:24

1 Answer 1

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Try
$ E_{min}b_{i,t-1} - \sum_{k=1}^{t-1}b_{i,k} \le E_{max}b_{i,t}$

$ \sum_t b_{i,t} \le E_{max}b_{i,t-1} - \sum_{k=1}^{t-1}b_{i,k}$

$ b_{i,t} \le 1 + b_{i,t-1} - b_{i,t-2}$

and ofcourse
$ b_{i,t} \le \sum_s a_{i,s,t} \le Tb_{i,t}$

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