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Drakhshan J. Hassan Feink M. Omer Esraa A. Haydier

Resumen

Abstract—In this study, the researcher endeavors to reduce the waiting time for beneficiaries (customers) in order to ensure beneficiary satisfaction and prevent them from leaving without receiving the service, thus solidifying their conviction to return to this service in the future. Quantitative methods and operations research are scientific approaches that assist decision-makers in making precise and objective decisions due to their capability to model and simplify complex problems. The issue of forming waiting queues is among the most prominent challenges that management in service organizations faces.


For the purpose of implementing the queuing model, data regarding the arrival of beneficiaries at the service station in the maternity hospital in Erbil Governorate were collected over a period of two years (2021 and 2022) by month. The data of arrivals and departures were tested using the (Goodness of Fit) test, revealing that the data follows a Poisson distribution. To apply queuing theory models, the selected model was the multi-service center model, given that the system consists of (3) delivery rooms in the hospital, and this specific room is considered the service hub.


Finally, a set of conclusions were reached, the most important of which is the probability that service centers (rooms) are occupied, which is a certain probability (1), The probability of no room being available in the hospital is equal to (0.36), indicating a weak probability concerning the studied phenomenon and the average number of newborn infants in the hospital (system) is (1).


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Keywords: The Concept of Queue Models, Reasons for the Appearance of Queue Models, Queue Models.


 

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Research Articles

Cómo citar

Hassan, D. J. ., Omer , F. M. ., & Haydier , E. A. . (2024). Using Queuing Theory to Choosing the Best Model for the Number of Recent Births and Deaths Data in Maternity Hospital - Erbil. Polytechnic Journal of Humanities and Social Sciences, 5(1), 678–683. https://doi.org/10.25156/ptjhss.v5n1y2024.pp678-683

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