Title: Queueing network model with jockeying to reduce the waiting time in the airport

Authors: K. Banu Priya; M. Sandeep Kumar; M. Geetha; J. Prabhu; V. Maheshwari; Sukumar Rajendran; M. Prasanna; P. Rajendran

Addresses: School of Advanced Sciences, Vellore Institute of Technology, Vellore, Tamil Nadu, India ' School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India ' School of Electronic Communication Engineering, Kalaignar Karunathi Institute of Technology, Coimbatore, India ' School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India ' School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India ' School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India ' School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India ' School of Advanced Sciences, Vellore Institute of Technology, Vellore, Tamil Nadu, India

Abstract: The airport queueing network model (AQNM) primary objective is to reduce the congestion and waste the passengers' time in the airport queues, mainly while crossing the checking baggage section, immigration, boarding, and leaving the system. In the AQNM model, every time the passenger notifies, the system moves slowly, and if the queue is multiserver, the passenger can use jockeying among the queues. If the queue is a single server queue, then jockeying is not possible. Additionally, a numerical example has worked with the Monte-Carlo simulation method for queueing theory and MatLab. To show the effect of the presented AQNM model, the results of waiting time without jockeying and waiting time with jockeying has been compared.

Keywords: queueing network; queueing theory; airport; jockeying; waiting time; Monte-Carlo method.

DOI: 10.1504/IJSSE.2021.121471

International Journal of System of Systems Engineering, 2021 Vol.11 No.3/4, pp.363 - 379

Received: 31 Jul 2020
Accepted: 17 Nov 2020
Published online: 14 Mar 2022 *

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