Flexible cyclic rostering in the service industry

Abstract

ABSTRACT Companies in the service industry frequently depend on cyclic rosters to schedule their workforce. Such rosters offer a high degree of fairness and long-term predictability of days on and off, but they can hinder an organization’s ability to respond to changing demand. Motivated by the need for improving cyclic planning at an airport ground handling company, this article introduces the idea of flexible cyclic rostering as a means of accommodating limited weekly adjustments of employee schedules. The problem is first formulated as a multi-stage stochastic program; however, this turned out to be computationally intractable. To find solutions, two approximations were developed that involved reductions to a two-stage problem. In the computational study, the flexible and traditional cyclic rosters derived from these approximations are compared and metrics associated with the value of stochastic information are reported. In the testing, we considered seven different perturbations of the demand curve that incorporate the types of uncertainty that are common throughout the service industry. To the best of our knowledge, this is the first analysis of cyclic rostering that applies stochastic optimization. The results show that a reduction in undercoverage of more than 10% on average can be achieved with minimal computational effort. It was also observed that the new approach can overcome most of the limitations of traditional cyclic rostering while still providing most of its advantages.