Interval-Constrained Bipartite Matching over Time (2402.18469v4)

Abstract: Interval-constrained online bipartite matching problem frequently occurs in medical appointment scheduling: unit-time jobs representing patients arrive online and are assigned to a time slot within their given time interval. We consider a variant of this problem where reassignments are allowed and extend it by a notion of current time, which is decoupled from the job arrival events. As jobs appear, the current point in time gradually advances. Jobs that are assigned to the current time unit become processed, which fixes part of the matching and disables these jobs or slots for reassignments in future steps. We refer to these time-dependent restrictions on reassignments as the over-time property. We show that FirstFit with reassignments according to the shortest augmenting path rule is $\frac{2}{3}$-competitive with respect to the matching cardinality, and that the bound is tight. Interestingly, this bound holds even if the number of reassignments per job is bound by a constant. For the number of reassignments performed by the algorithm, we show that it is in $\Omega(n \log n)$ in the worst case, where $n$ is the number of patients or jobs on the online side. This result is in line with lower bounds for the number of reassignments in online bipartite matching with reassignments, and, similarly to this previous work, we also conjecture that this bound should be tight. Moreover, we show that the algorithm maintaining the earliest-deadline-first order in the schedule yields maximum matchings, but at a cost of $\Omega(n^2)$ reassignments in worst case. Finally, we consider the generalization of the problem in which the set of feasible slots has arbitrary shape. We show that FirstFit retains its competitivity in this case and that no other deterministic algorithm can be more than $\frac{2}{3}$-competitive.