A model to simulate passenger flow congestion in airport environment
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2019-06-30 https://doi.org/10.14419/ijet.v7i4.19417 -
Passenger Flow, Airport Operational Planning, Airport Modelling, Simulation, Discrete Event Simulation -
Abstract
The global air transport industry is expanding rapidly. New approaches to airport management are required to ensure that ever-increasing consumer demand is met with adequate developments of ground operational and processing facilities; particularly those related to effective and safe processing of passenger flows. The solution to this problem requires, development of a new generation of fast, reliable, decision-making tools to quickly mobilise the human and technical resources available at modern airports. Opera-tional research aimed at developing novel airport optimization simulations to empower efficient management decisions is therefore a rapidly advancing field. The research conducted in this study highlighted the improvements to be made for better passenger flow modelling in airport environment. These models can be classified as either ‘analytical’, ‘simulation’, or ‘hybrid’ models, giving decision support capabilities at all levels of detail: from macroscopic, through mesoscopic, to microscopic. However, despite the current developments in understanding passenger flow, the literature suggests that an aggregate model, integrating both outbound and inbound processes, is still needed. The main aim of this research is to develop a generic, holistic simulation model that can optimise passenger flow that can be adopted in any airport environment. Included in this are major outbound and inbound processes such as check-in, security screening, and immigration. The model supports what-if and trade-off analyses by inclusion of a problem-oriented approach.
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References
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How to Cite
S. Alodhaibi, S., L. Burdett, R., & Kdv. Yarlagadda, P. (2019). A model to simulate passenger flow congestion in airport environment. International Journal of Engineering & Technology, 7(4), 6943-6946. https://doi.org/10.14419/ijet.v7i4.19417Received date: 2018-09-10
Accepted date: 2019-05-29
Published date: 2019-06-30