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Combining integer programming and the randomization method to schedule employees

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  • Ingolfsson, Armann
  • Campello, Fernanda
  • Wu, Xudong
  • Cabral, Edgar

Abstract

We 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.

Suggested Citation

  • Ingolfsson, Armann & Campello, Fernanda & Wu, Xudong & Cabral, Edgar, 2010. "Combining integer programming and the randomization method to schedule employees," European Journal of Operational Research, Elsevier, vol. 202(1), pages 153-163, April.
  • Handle: RePEc:eee:ejores:v:202:y:2010:i:1:p:153-163
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    References listed on IDEAS

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    Cited by:

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    2. Chen, Gang & Govindan, Kannan & Yang, Zhong-Zhen & Choi, Tsan-Ming & Jiang, Liping, 2013. "Terminal appointment system design by non-stationary M(t)/Ek/c(t) queueing model and genetic algorithm," International Journal of Production Economics, Elsevier, vol. 146(2), pages 694-703.
    3. 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.
    4. Defraeye, Mieke & Van Nieuwenhuyse, Inneke, 2016. "Staffing and scheduling under nonstationary demand for service: A literature review," Omega, Elsevier, vol. 58(C), pages 4-25.
    5. Tien Thanh Dam & Thuy Anh Ta & Tien Mai, 2022. "Joint chance-constrained staffing optimization in multi-skill call centers," Journal of Combinatorial Optimization, Springer, vol. 44(1), pages 354-378, August.
    6. Kaan Kuzu & Refik Soyer, 2018. "Bayesian modeling of abandonments in ticket queues," Naval Research Logistics (NRL), John Wiley & Sons, vol. 65(6-7), pages 499-521, September.
    7. Schwarz, Justus Arne & Selinka, Gregor & Stolletz, Raik, 2016. "Performance analysis of time-dependent queueing systems: Survey and classification," Omega, Elsevier, vol. 63(C), pages 170-189.
    8. Daniele Vigo & Claudio Caremi & Angelo Gordini & Sandro Bosso & Giuseppe D’Aleo & Beatrice Beleggia, 2014. "SPRINT: Optimization of Staff Management for Desk Customer Relations Services at Hera," Interfaces, INFORMS, vol. 44(5), pages 461-479, October.
    9. Örmeci, E. Lerzan & Salman, F. Sibel & Yücel, Eda, 2014. "Staff rostering in call centers providing employee transportation," Omega, Elsevier, vol. 43(C), pages 41-53.
    10. Ran Liu & Xiaolan Xie, 2018. "Physician Staffing for Emergency Departments with Time-Varying Demand," INFORMS Journal on Computing, INFORMS, vol. 30(3), pages 588-607, August.
    11. Samantha L. Zimmerman & Alexander R. Rutherford & Alexa Waall & Monica Norena & Peter Dodek, 2023. "A queuing model for ventilator capacity management during the COVID-19 pandemic," Health Care Management Science, Springer, vol. 26(2), pages 200-216, June.
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    13. Stefaan Haspeslagh & Patrick De Causmaecker & Andrea Schaerf & Martin Stølevik, 2014. "The first international nurse rostering competition 2010," Annals of Operations Research, Springer, vol. 218(1), pages 221-236, July.

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