Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/288361 
Authors: 
Year of Publication: 
2020
Citation: 
[Journal:] Journal of Scheduling [ISSN:] 1099-1425 [Volume:] 23 [Issue:] 5 [Publisher:] Springer US [Place:] New York, NY [Year:] 2020 [Pages:] 539-554
Publisher: 
Springer US, New York, NY
Abstract: 
In rotational workforce planning, a schedule is constructed from a sequence of work and rest periods. Each employee starts at a different part of the schedule, and after a certain amount of time, the schedule repeats. The length of the schedule increases with a higher number of employees. At the same time, various constraints on work sequences and days off have to be considered. For a large number of employees, it is difficult to construct a schedule that meets the requirements. It is important to ensure low solution times independently of the problem instance characteristics. In this work, a novel decomposition approach for rotational shift scheduling is proposed. The decomposition exploits the fact that most constraints in rotational workforce scheduling are imposed on the work shift sequence. By considering a fixed set of blocks to cover the demand, the problem complexity can be greatly reduced. Given a fixed set of blocks, we propose a network model that determines whether a feasible sequence of shift blocks exists. The decomposition approach is applied to the problem structure of the Rotating Workforce Scheduling Problem but may be extended to different problem structures. In a computational study, the decomposition approach is compared to a mathematical formulation and previous exact and heuristic approaches. Computational results show that the decomposition approach greatly outperforms previous heuristics on the standard benchmarks.
Subjects: 
Staff scheduling
Integer programming
Decomposition
Rotating Workforce Scheduling Problem
Persistent Identifier of the first edition: 
Creative Commons License: 
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Document Type: 
Article
Document Version: 
Published Version

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