Heuristics and Simulated Annealing Algorithm for the Surgical Scheduling Problem

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dc.authoridHancerliogullari, Gulsah/0000-0002-2551-541X|Koksalmis, Emrah/0000-0003-4922-2125|Hancerliogullari, Kadir Oymen/0000-0002-6856-4975
dc.authorwosidHancerliogullari, Kadir/AAN-4483-2021
dc.authorwosidHancerliogullari, Gulsah/S-5218-2016
dc.authorwosidHANCERLIOGULLARI KOKSALMIS, GULSAH/H-1579-2013
dc.contributor.authorHancerliogullari, Gulsah
dc.contributor.authorKoksalmis, Emrah
dc.contributor.authorHancerliogullari, Kadir Oymen
dc.coverage.doi10.1007/978-3-319-26024-2
dc.date.accessioned2024-07-18T20:40:06Z
dc.date.available2024-07-18T20:40:06Z
dc.date.issued2016
dc.departmentİstanbul Bilgi Üniversitesien_US
dc.description.abstractPlanning 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.en_US
dc.identifier.doi10.1007/978-3-319-26024-2_12
dc.identifier.endpage241en_US
dc.identifier.isbn978-3-319-26024-2
dc.identifier.isbn978-3-319-26022-8
dc.identifier.issn0884-8289
dc.identifier.scopus2-s2.0-84961358440en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage225en_US
dc.identifier.urihttps://doi.org/10.1007/978-3-319-26024-2_12
dc.identifier.urihttps://hdl.handle.net/11411/6981
dc.identifier.volume236en_US
dc.identifier.wosWOS:000371920400013en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofHeuristics, Metaheuristics and Approximate Methods in Planning and Schedulingen_US
dc.relation.publicationcategoryKitap Bölümü - Uluslararasıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectHealth Care Servicesen_US
dc.subjectSurgical Schedulingen_US
dc.subjectSimulated Annealingen_US
dc.subjectGreedy Heuristicen_US
dc.subjectMetaheuristicen_US
dc.subjectMathematical Programmingen_US
dc.subjectMonte-Carlo-Simulationen_US
dc.subjectOperating-Room Timeen_US
dc.subjectProgramming Approachen_US
dc.subjectAllocationen_US
dc.subjectHospitalsen_US
dc.subjectConstraintsen_US
dc.subjectStrategyen_US
dc.subjectTheateren_US
dc.subjectCostsen_US
dc.subjectUsageen_US
dc.titleHeuristics and Simulated Annealing Algorithm for the Surgical Scheduling Problem
dc.typeBook Chapter

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