Heuristics and Simulated Annealing Algorithm for the Surgical Scheduling Problem

Gulsah Hancerliogullari (), Emrah Koksalmis () and Kadir Oymen Hancerliogullari ()
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Gulsah Hancerliogullari: Istanbul Bilgi University
Emrah Koksalmis: Istanbul Technical University
Kadir Oymen Hancerliogullari: Giresun University

Chapter Chapter 12 in Heuristics, Metaheuristics and Approximate Methods in Planning and Scheduling, 2016, pp 225-241 from Springer

Abstract: 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.

Keywords: Health care services; Surgical scheduling; Simulated annealing; Greedy heuristic; Metaheuristic; Mathematical programming (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/978-3-319-26024-2_12

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