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A permutation flowshop model with time-lags and waiting time preferences of the patients

dc.contributor.advisorSamarghandi, Hamed
dc.contributor.advisorWilloughby, Keith
dc.contributor.committeeMemberHojati, Mehran
dc.contributor.committeeMemberAlmehdawe, Eman
dc.creatorRamezani, Iman
dc.date.accessioned2019-02-05T21:01:30Z
dc.date.available2020-02-05T06:05:10Z
dc.date.created2019-01
dc.date.issued2019-02-05
dc.date.submittedJanuary 2019
dc.date.updated2019-02-05T21:01:31Z
dc.description.abstractThe permutation flowshop is a widely applied scheduling model. In many real-world applications of this model, a minimum and maximum time-lag must be considered between consecutive operations. We can apply this model to healthcare systems in which the minimum time-lag could be the transfer times, while the maximum time-lag could refer to the number of hours patients must wait. We have modeled a MILP and a constraint programming model and solved them using CPLEX to find exact solutions. Solution times for both methods are presented. We proposed two metaheuristic algorithms based on genetic algorithm and solved and compared them with each other. A sensitivity of analysis of how a change in minimum and maximum time-lags can impact waiting time and Cmax of the patients is performed. Results suggest that constraint programming is a more efficient method to find exact solutions and changes in the values of minimum and maximum time-lags can impact waiting times of the patients and Cmax significantly.
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/10388/11872
dc.subjectWaiting times of the patients
dc.subjectHealthcare scheduling
dc.subjectConstraint programming
dc.subjectGenetic algorithm
dc.titleA permutation flowshop model with time-lags and waiting time preferences of the patients
dc.typeThesis
dc.type.materialtext
local.embargo.terms2020-02-05
thesis.degree.departmentFinance
thesis.degree.disciplineFinance
thesis.degree.grantorUniversity of Saskatchewan
thesis.degree.levelMasters
thesis.degree.nameMaster of Science (M.Sc.)

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