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University of Ontario Institute of Technology

Staffing queueing systems with cyclical demand and unreliable servers

Abstract

dc:description.abstract

Unplanned 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.

Degree

thesis:*
Name thesis:degree_name
Master of Science (MSc)
Discipline thesis:degree_discipline
Modelling and Computational Science
Grantor
University of Ontario Institute of Technology
Year dc:date.issued
2024

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Amini, Abraham
Advisor dc:contributor.advisor
  • Rastpour, Amir

Rights

Language dc:language.iso
en

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/10155/1815
OAI identifier oai:identifier
oai:ontariotechu.scholaris.ca:10155/1815

Chain of custody

source
Harvested from
Ontario Institute of Technology
Base URL
ontariotechu.scholaris.ca/server/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
related terms
citation

Amini, Abraham. Staffing queueing systems with cyclical demand and unreliable servers. University of Ontario Institute of Technology, 2024. https://hdl.handle.net/10155/1815