Combining integer programming and the randomization method to schedule employees
AbstractWe describe a method to find low cost shift schedules with a time-varying service level that is always above a specified minimum. Most previous approaches used a two-step procedure: (1) determine staffing requirements and (2) find a minimum cost schedule that provides the required staffing in every period. Approximations in the first step sometimes cause the two-step approach to find infeasible or suboptimal solutions. Our method iterates between a schedule evaluator and a schedule generator. The schedule evaluator calculates transient service levels using the randomization method and identifies infeasible intervals, where the service level is lower than desired. The schedule generator solves a series of integer programs to produce improved schedules, by adding constraints for every infeasible interval, in an attempt to eliminate infeasibility without eliminating the optimal solution. We present computational results for several test problems and discuss factors that make our approach more likely to outperform previous approaches.
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Bibliographic InfoArticle provided by Elsevier in its journal European Journal of Operational Research.
Volume (Year): 202 (2010)
Issue (Month): 1 (April)
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Web page: http://www.elsevier.com/locate/eor
Service operations management Employee scheduling Staffing requirements Nonstationary queues Randomization method Integer programming;
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- Van den Bergh, Jorne & Beliën, Jeroen & De Bruecker, Philippe & Demeulemeester, Erik & De Boeck, Liesje, 2013. "Personnel scheduling: A literature review," European Journal of Operational Research, Elsevier, vol. 226(3), pages 367-385.
- Izady, Navid & Worthington, Dave, 2012. "Setting staffing requirements for time dependent queueing networks: The case of accident and emergency departments," European Journal of Operational Research, Elsevier, vol. 219(3), pages 531-540.
- Defraeye, Mieke & Van Nieuwenhuyse, Inneke, 2011. "Setting staffing levels in an emergency department: opportunities and limitations of stationary queuing models," Open Access publications from Katholieke Universiteit Leuven urn:hdl:123456789/292344, Katholieke Universiteit Leuven.
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