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

• Published in: European journal of operational research 2014-04, Vol.234 (1), p.278-291
• Main Authors: Ladier, Anne-Laure, Alpan, Gülgün, Penz, Bernard
• Format: Article
• Language: English
• Subjects: Allocations; Computer Science; Contracts; Decision support systems; Freight forwarding; Handling equipment; Integer programming; Logistics; Manpower planning; Mathematical models; Mixed integer linear programming; Operations management; Operations Research; Scheduling; Sequential solving; Studies; Tasks; Working hours; Workload
• ISSN: 0377-2217; 1872-6860
• DOI: 10.1016/j.ejor.2013.10.023

•Timetabling and daily rostering application with the special constraints of logistics environment.•Optimization methods with three sequential mixed and integer linear programs.•Tool tested with industrial data and completely implemented at a logistics company.•Assessment of the robustness of the daily rostering when the input data changes. 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.