Sustainable Queuing-Network Design for Airport Security Based on the Monte Carlo Method

The design of airport queuing networks is a significant research field currently for researchers. Many factors must to be considered in order to achieve the optimized strategies, including the passenger flow volume, boarding time, and boarding order of passengers. Optimizing these factors lead to th...

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Veröffentlicht in:Sustainability 2018-01, Vol.10 (2), p.1
Hauptverfasser: Xu, Xiangqian, Zhou, Zhexuan, Dou, Yajie, Tan, Yuejin, Liao, Tianjun
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Zhou, Zhexuan
Dou, Yajie
Tan, Yuejin
Liao, Tianjun
description The design of airport queuing networks is a significant research field currently for researchers. Many factors must to be considered in order to achieve the optimized strategies, including the passenger flow volume, boarding time, and boarding order of passengers. Optimizing these factors lead to the sustainable development of the queuing network, which currently faces a few difficulties. In particular, the high variance in checkpoint lines can be extremely costly to passengers as they arrive unduly early or possibly miss their scheduled flights. In this article, the Monte Carlo method is used to design the queuing network so as to achieve sustainable development. Thereafter, a network diagram is used to determine the critical working point, and design a structurally and functionally sustainable network. Finally, a case study for a sustainable queuing-network design in the airport is conducted to verify the efficiency of the proposed model. Specifically, three sustainable queuing-network design solutions are proposed, all of which not only maintain the same standards of security, but also increase checkpoint throughput and reduce passenger waiting time variance.
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subjects Airline security
Airport design
Airport security
Boarding
Case studies
Computer simulation
Design
Monte Carlo simulation
Network design
Passengers
Queues
Queuing theory
Security
Sustainability
Sustainable development
title Sustainable Queuing-Network Design for Airport Security Based on the Monte Carlo Method
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