Suchergebnisse

With the increasing emphasis on improving service sector staff scheduling, many organisations have turned to employing part‐time staff in greater numbers. Operating managers need to schedule this staff in an efficient manner to cover the highly variable demand that is commonly present. This study demonstrates a number of important factors that influence how well staff schedules can be matched against variable demand. Four heuristic staff scheduling procedures are examined that provide optimal, or near optimal, staff schedules under different operating conditions. It is shown that variability in demand controls the number of excess staff hours scheduled, and that the smaller the number of daily shift hours and/or the number of days worked per week, the lower will be the level of excess staff hours scheduled.

Although research attention has been given to the modelling process
for simultaneous demand‐output management in manufacturing systems,
little interest has been demonstrated in service organisations despite
the fact that such organisations face unique conditions that further
complicate the demand‐output management issue. In response to this lack
of emphasis, we review the relevant research from both marketing and
operations management and present a cost‐effectiveness model for
balancing demand and service output.

ABSTRACTIn 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 system subject to demand variability. The manual heuristic proposed asigns full‐time empolyees 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.

ABSTRACTThis 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.