Abstract
This paper focuses on finding a satisfactory surgery scheduling to patients and efficiently managing scarce medical resources in laminar-flow operating theaters, which have distinct flow process and characteristics relative to general operating theaters and are widely used in China. The problem is solved in two phases. The first phase involves determining whether patients can be operated upon within the planning period and, if so, determining their surgery date with the objective of maximizing overall patient satisfaction. In the second phase, the surgery schedule consists of the surgery sequence and the corresponding operating room; with regard to the post-anesthesia care unit, a downstream resource, the daily scheduling problem is modeled as a two-stage no-wait hybrid flow-shop problem with the objective of minimizing the hospital’s operating costs, which includes the fixed costs of opening operating rooms, overtime costs and recovery costs. A discrete particle swarm optimization algorithm combined with heuristic rules is proposed. The results of experiments of our approach with realistic data show that our algorithm produced results of nearly the same quality as CPLEX but with a much less computation time. This approach can find the optimal number of daily functional operating rooms and recovery beds by varying parameters in the experiment, which gives management insights into reducing the operating costs of the hospital.
Similar content being viewed by others
References
Bowers J, Mould G (2005) Ambulatory care and orthopaedic capacity planning. Health Care Manag Sci 8(1):41–47
Cardoen B, Demeulemeester E, Beliën J (2009) Sequencing surgical cases in a daycare environment: an exact branch-and-price approach. Comput Oper Res 36(9):2660–2669
Cardoen B, Demeulemeester E, Beliën J (2009) Optimizing a multiple objective surgical case sequencing problem. Int J Prod Econ 119:354–366
Cardoen B, Demeulemeester E, Belien J (2010) Operating room planning and scheduling: a literature review. Eur J Oper Res 201:921–932
Chen CL, Huang SY, Tzeng YR, Chen CL (2013) A revised discrete particle swarm optimization algorithm for permutation flow-shop scheduling problem. Soft Comput. doi:10.1007/s00500-013-1199-z
Choong F, Phon-Amnuaisuk S, Alias MY (2011) Metaheuristic methods in hybrid flow shop scheduling problem. Expert Syst Appl 38(9):10787–10793
Coello Coello CA, Lechuga MS (2002) MOPSO: a proposal for multiple objective particle swarm optimization. Evol Comput 2:1051–1056
Denton BT, Miller AJ, Balasubramanian HJ, Huschka TR (2010) Optimal allocation of surgery blocks to operating rooms under uncertainty. Oper Res 58(4):802–816
Dexter F, Traub RD (2002) How to schedule elective surgical cases into specific operating rooms to maximize the efficiency of use of operating room time. Anesth Analg 94:933–942
Dexter F, Epstein RH (2005) Operating room efficiency and scheduling. Curr Opin Anaesthesiol 18:195–198
Dexter F, Marcon E (2006) Impact of surgical sequencing on post anesthesia care unit staffing. Health Care Manag Sci 9:87–98
Fei H, Meskens N, Chu C (2010) A planning and scheduling problem for an operating theatre using an open scheduling strategy. Comput Ind Eng 58:221–230
Fügener A, Hans EW, Kolisch R, Kortbeek N, Vanberkel PT (2014) Master surgery scheduling with consideration of multiple downstream units. Eur J Oper Res 239(1):227–236
Guinet A, Chaabane S (2003) Operating theatre planning. Int J Prod Econ 85:69–81
Gul S, Denton BT, Fowler JW, Huschka T (2011) Bi-criteria scheduling of surgical services for an outpatient procedure center. Prod Oper Manag 20(3):406–417
Gupta D (2007) Surgical suites’ operations management. Prod Oper Manag 16(6):689–700
Gupta D, Denton B (2010) Appointment scheduling in health care: challenges and opportunities. IIE Trans 40(9):800–819
Hsu V, de Matta R, Lee CY (2003) Scheduling patients in an ambulatory surgical center. Nav Res Logist 50:218–238
Hans E, Wullink G, Houdenhoven M, Kazemier G (2008) Robust surgery loading. Eur J Oper Res 185:1038–1050
Herroelen W, Leus R (2002) Project scheduling under uncertainty, survey and research potentials. Eur J Oper Res 165(2):289–306
Jebali A, Hadj Alouane AB (2006) Operating rooms scheduling. Int J Prod Econ 99:52–62
Kennedy J, Eberhart RC (1997) A discrete binary version of the particle swarm algorithm. Syst Man Cybern 5:4104–4108
Kuo RJ, Wang MJ, Huang TW (2011) An application of particle swarm optimization algorithm to clustering analysis. Soft Comput 15(3):533–542
Lamiri M, Xie X, Dolgui A, Grimaud F (2008) A stochastic model for operating room planning with elective and emergency demand for surgery. Eur J Oper Res 185:1026–1037
Liu B, Wang L, Jin Y (2007) An effective hybrid PSO-based algorithm for flow shop scheduling with limited buffers. Comput Oper Res 35:2791–2806
May JH, Spangler WE, Strum DP, Vargas LG (2011) The surgical scheduling problem: current research and future opportunities. Prod Oper Manag 20(3):392–405
Ozkarahan I (2000) Allocation of surgeries to operating rooms by goal programing. J Med Syst 24(6):339–378
Ogulata SN, Erol R (2003) A hierarchical multiple criteria mathematical programming approach for scheduling general surgery operations in large hospitals. J Med Syst 27(3):259–270
Pham DN, Klinkert A (2008) Surgical case scheduling as a generalized job shop scheduling problem. Eur J Oper Res 185:1011–1025
Schuster M, Standl T, Wagner JA, Berger J, Reimann MD (2004) Effect of Different Cost Drivers on Cost per Anesthesia Minute in Different Anesthesia Subspecialties. Anesthesiology 101(6):1435–1443
Shylo OV, Prokopyev OA, Schaefer AJ (2013) Stochastic operating room scheduling for high-volume specialties under block booking. INFORMS J Comput 25(4):682–692
Stuart K, Kozan E (2012) Reactive scheduling model for the operating theatre. Flex Serv Manuf J 24(4):400–421
Sier D, Tobin P, McGurk C (1997) Scheduling surgical procedures. J Oper Res Soc 48:884–891
Tang J, Song J (2010) Discrete particle swarm optimization combined with no-wait algorithm in stages for scheduling mill roller annealing process. Int J Comput Integr Manuf 23(11):979–991
Tassopoulos IX, Beligiannis GN (2012) Particle swarm optimization to solve effectively the school timetabling problem. Soft Comput 16(7):1229–1252
Xia W, Wu Z (2006) A hybrid particle swarm optimization approach for the jobshop scheduling problem. Int J Adv Manuf 29:360–366
Acknowledgments
The work is financially supported by the National Natural Science Foundation of China (NSFC 71021061) and the PhD program from MOE of China (No. 20120042110023).
Author information
Authors and Affiliations
Corresponding author
Additional information
Communicated by V. Loia.
Rights and permissions
About this article
Cite this article
Wang, Y., Tang, J., Pan, Z. et al. Particle swarm optimization-based planning and scheduling for a laminar-flow operating room with downstream resources. Soft Comput 19, 2913–2926 (2015). https://doi.org/10.1007/s00500-014-1453-z
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00500-014-1453-z