Staffing queueing systems with cyclical demand and unreliable servers

dc.contributor.advisorRastpour, Amir
dc.contributor.authorAmini, Abraham
dc.date.accessioned2024-08-27T14:04:19Z
dc.date.available2024-08-27T14:04:19Z
dc.date.issued2024-08-01
dc.degree.disciplineModelling and Computational Science
dc.degree.levelMaster of Science (MSc)
dc.description.abstractUnplanned staff absences, referring to scheduled servers being unavailable, pose significant challenges in sectors like healthcare, airlines, and correctional facilities, leading to under-staffing and management reliability issues. This thesis investigates the effectiveness of the Stationary Independent Period by Period (SIPP) method for staffing a multi-server delay queueing system with time-varying demand and server absence. Using the M(t)/M/c(t) queueing model, we systematically examine the SIPP method across various scenarios, including realistic ones, considering cyclical customer arrival rates and multiple servers with uncertain availability. We identify the parameter settings under which the SIPP method is most compromised. We propose two modifications to the SIPP method to account for absence in staffing decisions. We systematically compare these two proposed methods across different scenarios and identify the parameter settings under which each proposed method performs better. We also propose a heuristic to schedule additional servers given a certain budget.
dc.description.sponsorshipUniversity of Ontario Institute of Technology
dc.identifier.urihttps://ontariotechu.scholaris.ca/handle/10155/1815
dc.language.isoen
dc.subject.otherStaff absence
dc.subject.otherQueueing theory
dc.subject.otherStationary independent period by period method
dc.subject.otherMultiple servers
dc.subject.otherTime-varying customer arrival rates
dc.titleStaffing queueing systems with cyclical demand and unreliable servers
dc.typeThesis
thesis.degree.disciplineModelling and Computational Science
thesis.degree.grantorUniversity of Ontario Institute of Technology
thesis.degree.nameMaster of Science (MSc)

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