Open Access

Sören Merting, Martin Bichler, Aykut Uzunoglu

• Most organizations face distributed scheduling problems where private preferences of individuals mat­ter. Course assignment is a widespread example arising in educational institutions and beyond. Often students have preferences for course schedules over the week. First­Come­First­Served (FCFS) is the most widely used assignment rule in practice, but it is inefficient and unfair. Recent work on randomized match­ing suggests an alternative with attractive properties – Bundled Probabilistic Serial (BPS). A major chal­lenge in BPS is that the mechanism requires the participants’ preferences for exponentially many schedules. We describe a way to elicit preferences reducing the number of required parameters to a manageable set. We report results from field experiments, which allow us to analyze important empirical metrics of the as­ signments compared to FCFS. These metrics were central for the adoption of BPS at a major university. The overall system design yields an effective approach toMost organizations face distributed scheduling problems where private preferences of individuals mat­ter. Course assignment is a widespread example arising in educational institutions and beyond. Often students have preferences for course schedules over the week. First­Come­First­Served (FCFS) is the most widely used assignment rule in practice, but it is inefficient and unfair. Recent work on randomized match­ing suggests an alternative with attractive properties – Bundled Probabilistic Serial (BPS). A major chal­lenge in BPS is that the mechanism requires the participants’ preferences for exponentially many schedules. We describe a way to elicit preferences reducing the number of required parameters to a manageable set. We report results from field experiments, which allow us to analyze important empirical metrics of the as­ signments compared to FCFS. These metrics were central for the adoption of BPS at a major university. The overall system design yields an effective approach to solve daunting distributed scheduling tasks in organizations.…