The labor scheduling literature has demonstrated that the use of flexibility in designing employee schedules can result in a substantial improvement in labor utilization. This paper presents a new implicit integer linear programming formulation for the inclusion of meal/rest-break flexibility. Although the use of flexible break assignments in labor staffing decisions has been of research interest since an early article by Segal (1974), due to problem size, the majority of related research has involved the use of heuristics. An experimental analysis using four different labor requirements patterns and ten shift-length combinations demonstrated that, when flexible break assignments were modeled, the implicit formulation was superior to the traditional set-covering formulation with respect to 1) execution time, 2) computer memory requirements, and 3) the ability to produce optimal integer solutions to larger problems incorporating greater flexibility. Finally, a number of possible extensions of the implicit modeling approach for use in other labor scheduling environments are identified.service operations, labor scheduling, integer programming

This paper presents an initial study of relative performance for a number of the labor tour scheduling heuristic methods proposed in the literature. These heuristic methods were classified as either linear programming (LP) based or construction. Each of the methods was applied to a tour scheduling problem, subject to a variety of labor demand requirements distributions, with the singular objective being the minimization of total labor hours scheduled. Statistical analysis revealed that effective tour schedule solutions were generated by both LP-based and construction methods. Since the performances of the Keith [13], Morris and Showalter [18], and Bechtold and Showalter [5] methods were superior, their solutions were also compared across a number of secondary criteria. An overall analysis of the performances of these three methods resulted in the identification of a number of important managerial and decision-making issues. We conclude that service operations management should consider integrating these heuristic methods into a decision support system. Finally, suggestions for future research are provided.

In the increasingly competitive services sector, utilization of the labor force can make the difference between profits or losses. Until recently, service operations managers had a limited set of tools, most of them computer-based, for scheduling labor. This paper offers a manual heuristic for labor scheduling that outperforms traditional algorithmic solution approaches.Specifically, this study examines the problem of scheduling employees in service delivery systems subject to demand variability. The manual heuristic proposed assigns full-time employees to weekly work schedules with the objective of minimizing the total number of labor hours scheduled. The performance of the manual heuristic is compared to the classical algorithmic solution and to a lower bound for a variety of demand distributions and system operating conditions. The heuristic is shown to produce a smaller work force than the classical approach in 106 of the 108 demand-operating condition patterns examined.