Joint employee weekly timetabling and daily rostering: a decision-support tool for a logistics platform

Anne-Laure Ladier (), Gülgün Alpan () and Bernard Penz ()
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Anne-Laure Ladier: G-SCOP_GCSP - Gestion et Conduite des Systèmes de Production - G-SCOP - Laboratoire des sciences pour la conception, l'optimisation et la production - UJF - Université Joseph Fourier - Grenoble 1 - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - INPG - Institut National Polytechnique de Grenoble - CNRS - Centre National de la Recherche Scientifique
Gülgün Alpan: G-SCOP_GCSP - Gestion et Conduite des Systèmes de Production - G-SCOP - Laboratoire des sciences pour la conception, l'optimisation et la production - UJF - Université Joseph Fourier - Grenoble 1 - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - INPG - Institut National Polytechnique de Grenoble - CNRS - Centre National de la Recherche Scientifique
Bernard Penz: G-SCOP_GCSP - Gestion et Conduite des Systèmes de Production - G-SCOP - Laboratoire des sciences pour la conception, l'optimisation et la production - UJF - Université Joseph Fourier - Grenoble 1 - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - INPG - Institut National Polytechnique de Grenoble - CNRS - Centre National de la Recherche Scientifique

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Abstract: To deal with their highly variable workload, logistics companies make their task force flexible using multi-skilled employees, flexible working hours or short-term contracts. Together with the legal constraints and the handling equipments' capacities, these possibilities make personnel scheduling a complex task. This paper describes a model to support their chain of decisions from the weekly timetabling to the daily rostering (detailed task allocation). We divide the problem into three sub-problems depending on the type of decision to be made: (1) workforce dimensioning, (2) task allocation for a week, and (3) detailed rostering for a day. The three decisions are made sequentially, the output of a step being the input of the next one. Each step is modeled as a mixed integer linear program which is described and commented. The proposed models are tested with industrial data as well as generated instances. From the observations made in an industrial context, we show that our model is an actual management tool supporting the managers in their operational decisions. This tool is currently used by the company which provided us with the industrial data. Based on the results with the generated instances, we present the conditions under which the models can be solved within a reasonable amount of time, and we assess the robustness of the daily rostering when the input data changes.

Keywords: Mixed integer linear programming; Sequential solving; Logistics; Manpower planning (search for similar items in EconPapers)
Date: 2014
Note: View the original document on HAL open archive server: https://hal.science/hal-00881714v1
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Published in European Journal of Operational Research, 2014, 234 (1), pp.278-291. ⟨10.1016/j.ejor.2013.10.023⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-00881714

DOI: 10.1016/j.ejor.2013.10.023

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