Optimised buffer allocation to construct stable personnel shift rosters
Jonas Ingels and
Broos Maenhout
Omega, 2019, vol. 82, issue C, 102-117
Abstract:
Organisations need to construct stable baseline personnel shift rosters based on forecasts about the future personnel demand and employee availability. However, variability arises in the short-term, which renders these forecasts incorrect and affects the quality of the personnel roster. In this paper, we study how to anticipate this variability by introducing capacity buffers in the personnel shift roster. We propose a new approach by solving an equivalent deterministic formulation of a stochastic personnel shift scheduling problem. In contrast to traditional approaches, the size and position of capacity buffers are not defined in advance but are adequately determined as an endogenous variable by the proposed optimisation model to align the available personnel capacity to the stochastic demand. We propose different strategies to define the anticipated uncertainty and to allocate capacity buffers accordingly. We validate the performance of these strategies through a comparison with a deterministic minimum cost strategy and a more traditional resource buffer strategy based on a three-step methodology. This methodology makes use of simulation and optimisation to mimic the hierarchical personnel planning process.
Keywords: Personnel shift scheduling; Operational variability; Roster stability; Capacity buffers (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0305048316303991
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:jomega:v:82:y:2019:i:c:p:102-117
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01
DOI: 10.1016/j.omega.2017.12.006
Access Statistics for this article
Omega is currently edited by B. Lev
More articles in Omega from Elsevier
Bibliographic data for series maintained by Catherine Liu ().