In the context of scheduling maintenance jobs on arcs of a flow network I came across the problem to schedule jobs, indexed by $j$, and given by triples $(r_j,d_j,p_j)$ of (integer) release time, due time and processing time such that the total time in which no job is processed is maximized. A schedule is given by start times $x_j\in S_j:=\{r_j,r_j+1,\ldots,d_j-p_j+1\}$. For instance, for five jobs with $(r_j,d_j,p_j)$ equal to \[(1,3,3),\ (20,22,3),\ (10,11,2),\ (1,18,5),\ (8,26,5)\] and a time horizon of 30, the first three jobs are fixed starting at times $x_1=1$, $x_2=20$ and $x_3=10$, and for the last two jobs it is optimal to start both of them at the same time $x_4=x_5\in\{8,9,10\}$. The objective value (number of time periods without any job) is \[30-3-5-3=19.\]
The straightforward binary program for $n$ jobs looks as follows ($y_t$ is the indicator variable for the activity of the "plant" machine suggested in the comment by András Salamon) \begin{align*} \text{minimize}\ \sum_{t=1}^Ty_t&\\ \text{subject to}\qquad \sum_{t\in S_j}x_{jt} &=1 && j\in[n], \\ y_t-\sum_{t'\in S_j\cap[t-p_j+1,t]}x_{jt'} &\geqslant 0 && t\in[T],\ j\in J_t,\\ x_{jt}&\in\{0,1\} && j\in[n],\ t\in S_j,\\ y_t &\in\{0,1\} && t\in[T]. \end{align*} Here $J_t=\{j\ :\ r_j\leqslant t\leqslant d_j\}$ denotes the set of jobs that can be "active" at time $t$. Interestingly, the constraint matrix is not totally unimodular in general, but the LP relaxation seems to have always integer optimal solutions. Writing down the dual also yields a problem which can be interpreted combinatorially, but so far I haven't been able to turn this into an integrality proof.
One can look at variants of the problem where the number of jobs that can be processed simultaneously is bounded, or there is a given partition of the job set such that no two jobs from the same part can be processed at the same time. Has this kind of objective function been studied in the scheduling literature? Or is there any other related problem?
