A Two Level Hybrid Bees Algorithm for Operating Room Scheduling Problem

  • Lamya Ibrahim AlmaneeaEmail author
  • Manar Ibrahim Hosny
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 858)


In patients’ healthcare, manual planning of operating rooms is very difficult due to having a large number of constraints that the planner should take into consideration. The aim of this paper is to solve the operating room scheduling problem using a hybrid Bees Algorithm. Our focus is to solve a two-level variant of the problem, the Master Surgery Scheduling Problem and the Surgical Case Assignment Problem, where both hospital cost and patient cost are considered. We use a hybrid population based meta-heuristic, namely, a Hybrid BA with Simulated Annealing. The performance of our algorithm is compared against a Tabu Search single solution based method from the literature using the same test data. The experimental results demonstrate the advantages of using our proposed approach.


Operating room scheduling Surgical Case Assignment Problem Meta-heuristics Bees algorithm Simulated annealing 


  1. 1.
    Aringhieri, R., Landa, P., Soriano, P., Tànfani, E., Testi, A.: A two level metaheuristic for the operating room scheduling and assignment problem. Comput. Oper. Res. 54, 21–34 (2015)MathSciNetCrossRefGoogle Scholar
  2. 2.
    Cardoen, B., Demeulemeester, E., Beliën, J.: Operating room planning and scheduling: a literature review. Eur. J. Oper. Res. 201(3), 921–932 (2010)CrossRefGoogle Scholar
  3. 3.
    Garey, M.R., Johnson, D.S.: A guide to the theory of NP-completeness. WH Free N. Y., 70 (1979)Google Scholar
  4. 4.
    Talbi, E.-G.: Metaheuristics: from Design to Implementation, vol. 74. Wiley (2009)Google Scholar
  5. 5.
    Pham, T., Ghanbarzadeh, A., Koc, E., Otri, S., Rahim, S., Zaidi, M.: The Bees Algorithm, Technical report. Cardiff Manufacturing Engineering Centre at Cardiff University (2005)Google Scholar
  6. 6.
    Fei, H., Meskens, N., Chu, C.: An operating theatre planning and scheduling problem in the case of a “block scheduling” strategy. In: Proceedings of International Conference on Service Systems and Service Management, vol. 1, pp. 422–428 (2006)Google Scholar
  7. 7.
    Liu, Y., Chu, C., Wang, K.: A new heuristic algorithm for the operating room scheduling problem. Comput. Ind. Eng. 61(3), 865–871 (2011)CrossRefGoogle Scholar
  8. 8.
    Perdomo, V., Augusto, V., Xie, X.: Operating theatre scheduling using lagrangian relaxation. In: Proceedings of International Conference on Service Systems and Service Management, vol. 2, pp. 1234–1239 (2006)Google Scholar
  9. 9.
    Denton, B., Viapiano, J., Vogl, A.: Optimization of surgery sequencing and scheduling decisions under uncertainty. Health Care Manag. Sci. 10(1), 13–24 (2007)CrossRefGoogle Scholar
  10. 10.
    Hans, E., Wullink, G., Van Houdenhoven, M., Kazemier, G.: Robust surgery loading. Eur. J. Oper. Res. 185(3), 1038–1050 (2008)CrossRefGoogle Scholar
  11. 11.
    Fei, H., Chu, C., Meskens, N., Artiba, A.: Solving surgical cases assignment problem by a branch-and-price approach. Int. J. Prod. Econ. 112(1), 96–108 (2008)CrossRefGoogle Scholar
  12. 12.
    Krempels, K.-H., Panchenko, A.: An approach for automated surgery scheduling. In: Proceedings of the Sixth International Conference on the Practice and Theory of Automated Timetabling, pp. 209–233 (2006)Google Scholar
  13. 13.
    Cardoen, B., Demeulemeester, E., Beliën, J.: Optimizing a multiple objective surgical case sequencing problem. Int. J. Prod. Econ. 119(2), 354–366 (2009)CrossRefGoogle Scholar
  14. 14.
    Cardoen, B., Demeulemeester, E., Beliën, J.: Scheduling surgical cases in a day-care environment: a branch-and-price approach (2007)Google Scholar
  15. 15.
    Blake, J.T., Donald, J.: Mount Sinai hospital uses integer programming to allocate operating room time. Interfaces 32(2), 63–73 (2002)CrossRefGoogle Scholar
  16. 16.
    Beliën, J., Demeulemeester, E.: Building cyclic master surgery schedules with leveled resulting bed occupancy. Eur. J. Oper. Res. 176(2), 1185–1204 (2007)CrossRefGoogle Scholar
  17. 17.
    Testi, A., Tanfani, E., Torre, G.: A three-phase approach for operating theatre schedules. Health Care Manag. Sci. 10(2), 163–172 (2007)CrossRefGoogle Scholar
  18. 18.
    Jebali, A., Alouane, A.B.H., Ladet, P.: Operating rooms scheduling. Int. J. Prod. Econ. 99(1), 52–62 (2006)CrossRefGoogle Scholar
  19. 19.
    Testi, A., Tanfani, E., Valente, R., Ansaldo, G.L., Torre, G.C.: Prioritizing surgical waiting lists. J. Eval. Clin. Pract. 14(1), 59–64 (2008)CrossRefGoogle Scholar
  20. 20.
    Tànfani, E., Testi, A.: A pre-assignment heuristic algorithm for the Master Surgical Schedule Problem (MSSP). Ann. Oper. Res. 178(1), 105–119 (2010)MathSciNetCrossRefGoogle Scholar
  21. 21.
    Masmoudi, M.A., Hosny, M., Braekers, K., Dammak, A.: Three effective metaheuristics to solve the multi-depot multi-trip heterogeneous dial-a-ride problem. Transp. Res. Part E Logist. Transp. Rev. 96, 60–80 (2016)CrossRefGoogle Scholar
  22. 22.
    Kirkpatrick, S.: Optimization by simulated annealing: Quantitative studies. J. Stat. Phys. 34(5), 975–986 (1984)MathSciNetCrossRefGoogle Scholar
  23. 23.
    Lin, S.-W., Vincent, F.Y.: A simulated annealing heuristic for the multiconstraint team orienteering problem with multiple time windows. Appl. Soft Comput. 37, 632–642 (2015)CrossRefGoogle Scholar
  24. 24.
    Xiao, Y., Konak, A.: A simulating annealing algorithm to solve the green vehicle routing & scheduling problem with hierarchical objectives and weighted tardiness. Appl. Soft Comput. 34, 372–388 (2015)CrossRefGoogle Scholar
  25. 25.
    Touihri, A., Dridi, O., Krichen, S.: A multi operator genetic algorithm for solving the capacitated vehicle routing problem with cross-docking problem. In: Proceedings of IEEE Symposium Series on Computational Intelligence (SSCI), pp. 1–8 (2016)Google Scholar
  26. 26.
    Behdadnia, M., Askerzade, I.: Simulated Annealing Approach for Solving a Time Dependent Orienteering Problem (2016)Google Scholar
  27. 27.
    Metropolis, N., Rosenbluth, A.W., Rosenbluth, M.N., Teller, A.H., Teller, E.: Equation of state calculations by fast computing machines. J. Chem. Phys. 21(6), 1087–1092 (1953)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Computer Science Department, College of Computer and Information SciencesKing Saud University, KSURiyadhSaudi Arabia

Personalised recommendations