Stochastic Modeling for Optimal Batch Scheduling of Prophylactic Dispensing Centers

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dc.contributor.advisor Dr. Brian T. Denton, Committee Chair en_US
dc.contributor.advisor Dr. Julie S. Ivy, Committee Member en_US
dc.contributor.advisor Dr. Yahya Fathi, Committee Member en_US
dc.contributor.author Moomaw, Lindsay M. en_US
dc.date.accessioned 2010-08-19T18:18:35Z
dc.date.available 2010-08-19T18:18:35Z
dc.date.issued 2010-04-09 en_US
dc.identifier.other etd-03262010-132747 en_US
dc.identifier.uri http://www.lib.ncsu.edu/resolver/1840.16/6270
dc.description.abstract We study stochastic optimization models for scheduling batch arrivals to a Point of Dispensing (POD) in response to a biological emergency in which mass vaccination or dispensing of antiviral medication is implemented. The objective of our model is to minimize the total expected waiting time for customers and idle time of servers while considering the stochasticity of service times and customer flow through the POD. We begin with a simplified design of a POD which includes three function-defined servers and the basic queuing elements that would be utilized in a realistic POD, including splitting and merging queues. We create two-stage stochastic programming formulations to model two cases. In the first case of splitting queues, numerical results suggest an optimal constant batch interarrival time can produce total expected waiting and idle time costs near those of the optimal solution to the stochastic program. Stochastic programming formulations for the second case of split and merged queues prove to be more difficult. We study information and integer relaxations which provide approximations that are easier to solve. However, our results indicate relatively wide gaps on the optimal solution value. We expand the POD design to include eight stations to better represent a realistic facility. Using discrete event simulation, we test two batch interarrival time heuristics and report the similarity in their best solutions with respect to lowest expected costs of waiting and total operating time. en_US
dc.rights I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dis sertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to NC State University or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. en_US
dc.subject stochastic programming en_US
dc.subject simulation en_US
dc.subject emergency response en_US
dc.subject pandemic influenza en_US
dc.subject point of dispensing en_US
dc.title Stochastic Modeling for Optimal Batch Scheduling of Prophylactic Dispensing Centers en_US
dc.degree.name MS en_US
dc.degree.level thesis en_US
dc.degree.discipline Industrial Engineering en_US


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