Modeling and solving a real-life multi-skill shift design problem
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In this work, we consider the shift design problem and we define a novel, complex formulation arising from practical cases. In addition, we propose a new search method based on a fast Simulated Annealing, that, differently from previous approaches, solves the overall problem as a single-stage procedure. The core of the method is a composite neighborhood that includes at the same time changes in the staffing of shifts, the shape of shifts, and the position of breaks. Finally, we present a statistically-principled experimental analysis on a set of instances obtained from real cases. Both instances and results are available on the web for future comparisons.
KeywordsShift design Workforce scheduling Simulated annealing Local search
Nysret Musliu has been supported for this work by the Austrian Science Fund (FWF): P24814-N23.
- Aarts, E. H. L., & Korst, J. (1989). Simulated annealing and Boltzmann machines. New York: Wiley.Google Scholar
- Beer, A., Gärtner, J., Musliu, N., Schafhauser, W., & Slany, W. (2008). Scheduling breaks in shift plans for call centers. In Proceedings of The 7th international conference on the practice and theory of automated timetabling. Montreal, Canada.Google Scholar
- Birattari, M. (2004). The problem of tuning metaheuristics as seen from a machine learning perspective, PhD thesis. Belgium: Université Libre de Bruxelles.Google Scholar
- Černý, V. (1985). Thermodynamical approach to the traveling salesman problem: An efficient simulation algorithm. Journal of Optimization Theory and Applications, 45(l), 41–51.Google Scholar
- Dantzig, G. B. (1954). A comment on Eddie’s traffic delays at toll booths. Operations Research, 2, 339–341.Google Scholar
- Gärtner, J., Musliu, N., & Slany, W. (2004). A heuristic based system for generation of shifts with breaks. In Proceedings of the 24th SGAI international conference on innovative techniques and applications of artificial intelligence, Cambridge.Google Scholar
- Tellier, P., & White, G. (2006). Generating personnel schedules in an industrial setting using a tabu search algorithm. In E. K. Burke & H. Rudova (Eds.), In The 5th international conference on the practice and theory of automated timetabling (pp. 293–302).Google Scholar
- Urli, T. (2013). json2run: A tool for experiment design & analysis. arXiv:1305.1112.