A two-stage solution approach for personalized multi-department multi-day shift scheduling |
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| Affiliation: | 1. Université Laval, 2325 rue de la Terrasse, Québec G1V 0A6, Canada;2. CIRRELT, Université Laval, Pavillon Palasis-Prince, bureau 2415, 2325 rue de la Terrasse, Québec G1V 0A6, Canada;3. École Polytechnique de Montréal, C.P. 6079, succursale Centre-ville, Montréal H3C 3A7, Canada;4. GERAD, 3000 chemin de la Côte-Sainte-Catherine, Montréal H3T 2A7, Canada;1. Department of Economics and Business, University of Catania, Corso Italia, 55, 95129, Catania, Italy;2. Portsmouth Business School, Centre for Operational Research and Logistics (CORL), University of Portsmouth, Portsmouth, United Kingdom;1. HEC Liège, Management School of the University of Liège, Liège, Belgium;2. School of Business and Economics, Maastricht University, Maastricht, the Netherlands;1. Department of Mathematics, Technische Universität Kaiserslautern, Kaiserslautern 67663 Germany;2. CEG-IST, Instituto Superior Técnico, Universidade de Lisboa, Lisboa 1049-001, Portugal;1. Department of Industrial and Systems Engineering, University of Florida, 303 Weil Hall, Gainesville, FL 32611, USA;2. Department of Industrial Engineering and Management Systems, University of Central Florida, 12800 Pegasus Dr., Orlando, FL 32816, USA;3. Department of Industrial Engineering, University of Pittsburgh, 1048 Benedum Hall, Pittsburgh, PA 15261, USA |
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| Abstract: | In this paper, we address a personalized multi-department multi-day shift scheduling problem with a multi-skill heterogeneous workforce where employees can be transferred between departments under some restrictions. The objective is to construct a schedule that minimizes under-coverage, over-coverage, transfer and labor costs. We propose a novel two-stage approach to solve it: the first stage considers an approximate and smaller problem based on data aggregation and produces approximate transfers. The second stage constructs personalized schedules based on the information deduced from the first stage. An exhaustive experimental study is conducted and proves the efficiency of the proposed approach in terms of solution quality and computing times. |
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