General Information
    • ISSN: 1793-8201 (Print), 2972-4511 (Online)
    • Abbreviated Title: Int. J. Comput. Theory Eng.
    • Frequency: Quarterly
    • DOI: 10.7763/IJCTE
    • Editor-in-Chief: Prof. Mehmet Sahinoglu
    • Associate Editor-in-Chief: Assoc. Prof. Alberto Arteta, Assoc. Prof. Engin Maşazade
    • Managing Editor: Ms. Mia Hu
    • Abstracting/Indexing: Scopus (Since 2022), INSPEC (IET), CNKI,  Google Scholar, EBSCO, etc.
    • Average Days from Submission to Acceptance: 192 days
    • E-mail: ijcte@iacsitp.com
    • Journal Metrics:

Editor-in-chief
Prof. Mehmet Sahinoglu
Computer Science Department, Troy University, USA
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.

IJCTE 2021 Vol.13(3): 61-67 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2021.V13.1291

Increase the System Utilization by Adaptive Queue Management System with Time Restricted Reservation

V. Limlawan and P. Anussornnitisarn

Abstract—Traditionally, the ticket queue technology is implemented to manage queuing system, but the disadvantage of the ticket queue is losing queue information. The queue-length and the waiting time is often overestimated when some customer abandons from the queue. The overestimated waiting time intensify the customer abandonment problem which has negatively effects on business revenue and the resource utilization. Based on the problem, this paper aims to study the adaptive queue management system with the queue reservation system and also proposed the time restriction rule for the reservation. In the system the queue information such as queue-length and service time is constantly updated, and the system is allowed customer to reserve the queue if the waiting time is too long. Moreover, the time restriction rule prevents the reservation which affects the system performance. The result shows that the adaptive queue management system with the queue reservation and the time restriction rule outperforms the system without the queue reservation and the time restriction rule. In most cases, the resource utilization of the system is 0.9, and the percentage of customer completed service is more than 90%.

Index Terms—Artificial neural network, exponential weight moving average control chart, queue management system, adaptive system.

Varis Limlawan is with International Graduate Program in Industrial Engineering, Faculty of Engineer, Kasetsart University, Thailand (e-mail: varis.lw@gmail.com). Pornthep Anussornnitisarn is with Department of Industrial Engineering, Faculty of Engineer, Kasetsart University, Thailand (e-mail: fengpta@ku.ac.th).

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Cite:V. Limlawan and P. Anussornnitisarn, "Increase the System Utilization by Adaptive Queue Management System with Time Restricted Reservation," International Journal of Computer Theory and Engineering vol. 13, no. 3, pp. 61-67, 2021.

Copyright © 2021 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).


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