An investigation of shift and break flexibility with real-time break assignments using a rolling horizon approach

Youngbum Hur (), Jonathan F. Bard (), Markus Frey () and Ferdinand Kiermaier ()
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Youngbum Hur: The University of Texas
Jonathan F. Bard: The University of Texas
Markus Frey: Technical University of Munich
Ferdinand Kiermaier: Technical University of Munich

Flexible Services and Manufacturing Journal, 2019, vol. 31, issue 1, No 7, 174-211

Abstract: Abstract The purpose of this paper is to investigate the benefits that flexibility offers in daily shift scheduling, especially when demand is uncertain. The different forms of flexibility considered include shift start times, the number of breaks, break lengths, and break placement. Five related mixed-integer programming models are developed and used to compare break scheduling in advance and either sequentially or in real time for various shift and break profiles. The first model integrates the shift and break assignments while the second model assigns shifts only. The third and fourth models assume an optimal set of shifts. In the former case, the goal is to assign as many breaks as possible without violating demand requirements; in the latter case, the objective is to minimize undercoverage while ensuring that all shifts receive their required breaks. The fifth model takes a rolling horizon approach and provides the greatest advantage when responding to unexpected demand fluctuations over the day. Tests were performed using work requirements for ground handlers at a major European airport and showed in part that when demand is known and the most flexible break type is used, the total uncovered periods in a day can be decreased by up to 94% (down from 270 to 16). When demand is uncertain, we found that using our rolling horizon procedure reduces undercoverage by up to 41% compared to scheduling breaks in advance.

Keywords: Shift scheduling; Flexible breaks; Rolling horizon framework; Uncertain demand; Real-time break assignments (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10696-018-9305-2

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