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Heuristics and Simulated Annealing Algorithm for the Surgical Scheduling Problem

In: Heuristics, Metaheuristics and Approximate Methods in Planning and Scheduling

Author

Listed:
  • Gulsah Hancerliogullari

    (Istanbul Bilgi University)

  • Emrah Koksalmis

    (Istanbul Technical University)

  • Kadir Oymen Hancerliogullari

    (Giresun University)

Abstract

Planning and scheduling play a very important role in health care. Effective scheduling optimizes the utilization of scarce resources such as operating rooms (ORs), devices in hospitals, and surgeons. Therefore, operations research/operations management techniques have been frequently used in health care systems management. In this chapter, we examine the surgical scheduling problem over multiple operating rooms. In order to find an optimal solution to surgical scheduling problem, mixed-integer programming (MIP) formulation of the surgical scheduling problem is presented. The model includes constraints for several operational rules and requirements found in most hospitals, and specifically minimizes the total weighted start time as a performance measure (or objective function). Since the problem is known to be an NP-hard in most of its forms, heuristic algorithms (i.e., greedy heuristics and a metaheuristic) are also introduced to find near-optimal solutions efficiently.

Suggested Citation

  • Gulsah Hancerliogullari & Emrah Koksalmis & Kadir Oymen Hancerliogullari, 2016. "Heuristics and Simulated Annealing Algorithm for the Surgical Scheduling Problem," International Series in Operations Research & Management Science, in: Ghaith Rabadi (ed.), Heuristics, Metaheuristics and Approximate Methods in Planning and Scheduling, edition 1, chapter 0, pages 225-241, Springer.
    • Handle: RePEc:spr:isochp:978-3-319-26024-2_12
    DOI: 10.1007/978-3-319-26024-2_12
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    Cited by:

    1. Sean Harris & David Claudio, 2022. "Current Trends in Operating Room Scheduling 2015 to 2020: a Literature Review," SN Operations Research Forum, Springer, vol. 3(1), pages 1-42, March.

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