A study on single server and multi server fuzzy queuing model and queuing theory model / Muhammad Alif Haikal Nor Azman, Nurul Latifah Ramli and Nurazimah Maharudin

People always need to face with a long queue and waiting for a long time to be served. Usually, in the peak hours such as 12 p.m. until 2 p.m., 6 p.m. until 10 p.m. are always full of people and the long queue continues until the peak hours end. It can lead to dissatisfaction of customers. By com...

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Bibliographic Details
Main Authors: Nor Azman, Muhammad Alif Haikal, Ramli, Nurul Latifah, Maharudin, Nurazimah
Format: Student Project
Language:en
Published: 2019
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/37312/1/37312.pdf
https://ir.uitm.edu.my/id/eprint/37312/
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Summary:People always need to face with a long queue and waiting for a long time to be served. Usually, in the peak hours such as 12 p.m. until 2 p.m., 6 p.m. until 10 p.m. are always full of people and the long queue continues until the peak hours end. It can lead to dissatisfaction of customers. By comparing Fuzzy Queuing Model and Queuing Theory Model which model is the best model to get the better service performance. The purpose of this study is to investigate the service performance of cinema using fuzzy queuing model. This study suggests several research objectives to be attained which are to compute service performance using Fuzzy Queuing Model for single server and multiserver. Other than that, is to compare service performance between Fuzzy Queuing Model and Queuing Theory Model. The method that we used in this study are Queuing Theory Model and Fuzzy Queuing Model which is DSW algorithm to get the required variables. The data was collected manually at GSC Cinemas Palm Mall Seremban and TGV Cinemas, Aeon Seremban 2. The values of arrival rate, A and service rate, μ were obtained by calculation with using Queuing Theory Model and Fuzzy Queuing Model. For future observation, other researcher can compare single server for both methods to know which method the best method in maximize the service performance and minimize the service time.