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dc.contributor.advisorSattar, Abdul
dc.contributor.authorShahabiKargar, Zahra
dc.date.accessioned2018-01-23T02:54:46Z
dc.date.available2018-01-23T02:54:46Z
dc.date.issued2016
dc.identifier.doi10.25904/1912/3675
dc.identifier.urihttp://hdl.handle.net/10072/367615
dc.description.abstractScheduling problems emerge almost everywhere in real world situations. Efficient scheduling of resources in dynamic complex real world environments continues to pose a significant research challenge. Every real world problem has its own idiosyn- crasies, and environments in the real world are often more complicated. In real world dynamic environments, inevitable and unpredictable real-time events often force a change in scheduled plans. Despite this, most current approaches have been focused on solving simplified scheduling models assuming that all problem characteristics are known in advance. As the hospital’s largest revenue and cost centre, operating rooms are of pivotal importance to hospitals. Any improvement of surgery delivery systems is particularly important for hospitals. With healthcare starting to buckle under the pressures of growing demand and encumbered resources, improving operating room scheduling to deliver a significant improvement in utilisation of this overburdened resource is more important than ever. Motivated with this need, this dissertation describes our efforts to deliver significant improvements to operating room scheduling processes, particularly in Australian public hospitals.
dc.languageEnglish
dc.publisherGriffith University
dc.publisher.placeBrisbane
dc.rights.copyrightThe author owns the copyright in this thesis, unless stated otherwise.
dc.subject.keywordsHospital operating room schedules
dc.subject.keywordsPublic hospital room schedules
dc.subject.keywordsPublic hospital operations
dc.titleIntelligent Scheduling for Hospital Operating Rooms
dc.typeGriffith thesis
gro.facultyScience, Environment, Engineering and Technology
gro.rights.copyrightThe author owns the copyright in this thesis, unless stated otherwise.
gro.hasfulltextFull Text
dc.contributor.otheradvisorKhanna, Sankalp
dc.contributor.otheradvisorLind, James
dc.rights.accessRightsPublic
gro.identifier.gurtIDgu1493949478510
gro.source.ADTshelfnoADT0
gro.source.GURTshelfnoGURT
gro.thesis.degreelevelThesis (PhD Doctorate)
gro.thesis.degreeprogramDoctor of Philosophy (PhD)
gro.departmentInstitute for Integrated and Intelligent Systems
gro.griffith.authorShahabi Kargar, Zahra


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