http://www3.eng.cam.ac.uk/~hj231/Papers/rostering.pdf

Staff scheduling and rostering: A review of applications, methods and models

Quality function deployment: A literature review

Nurse rostering is a complex scheduling problem that affects hospital personnel on a daily basis all over the world. The need for quality software solutions is acute for a number of reasons. In particular, it is very important to efficiently utilise time and effort, to evenly balance the workload among people and to attempt to satisfy personnel preferences. A high quality roster can lead to a more contented and thus more effective workforce.

In this review, we discuss nurse rostering within the global personnel scheduling problem in healthcare. We begin by briefly discussing the review and overview papers that have appeared in the literature and by noting the role that nurse rostering plays within the wider context of longer term hospital personnel planning. The main body of the paper describes and critically evaluates solution approaches which span the interdisciplinary spectrum from operations research techniques to artificial intelligence methods. We conclude by drawing on the strengths and weaknesses of the literature to outline the key issues that need addressing in future nurse rostering research.

/pdf/the-state-of-the-art-of-nurse-rostering-4uxzrvsub8.pdf

The State of the Art of Nurse Rostering

Personnel scheduling: A literature review

The asymmetric relationship between attribute-level performance and overall customer satisfaction: a reconsideration of the importance–performance analysis

Services and products possess various attributes, some being more important than others. Importance-Performance Analysis (IPA) is a technique for prioritising attributes based on measurements of performance and importance. A weakness of IPA is that it conceptualises attribute importance as a scalar which is independent of attribute performance. In this article we theorise that importance is not adequately represented as a point estimate, but is a function of performance. When attribute performance changes, importance does also, which can change the relative priority of subsequent improvement efforts. Empirical results are presented which support our theory, The nature of the performance-importance response function is discussed, along with implications. Ideas for future research are also discussed, including application of the findings to quality modelling (SERVQUAL) and other decision support methodologies (Quality Function Deployment and the Analytic Hierarchy Process).

The Performance-Importance Response Function: Observations and Implications

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.

A Comparative Evaluation of Labor Tour Scheduling Methods

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 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.

A methodology for labor scheduling in a service operating system

Measuring the impact of part-time workers in service organizations

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.

Michael J. Showalter

Papers

The Performance-Importance Response Function: Observations and Implications

A Comparative Evaluation of Labor Tour Scheduling Methods

A methodology for labor scheduling in a service operating system

Measuring the impact of part-time workers in service organizations

An Evaluation of a Full‐/Part‐time Tour Scheduling Methodology