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An operations research model for the evaluation of an airport terminal: SLAM (simple landside aggregate model)

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  • Brunetta, Lorenzo
  • Righi, Luca
  • Andreatta, Giovanni

Abstract

The Simple Landside Aggregate Model (SLAM) is a model for estimating capacity and delays in airport passenger terminals. SLAM is designed to answer “what if†questions about alternative configurations of the various processing and holding facilities in a terminal. It consists of a network of modules, one for each facility of the terminal. These modules are based on a set of quite simple mathematical formulas to be used for the estimation of the capacity of each facility (in terms of passengers per hour) and the level of service (LOS) associated with it. LOS is quantified both in terms of “space available per facility occupant†and waiting time for being processed.

Suggested Citation

  • Brunetta, Lorenzo & Righi, Luca & Andreatta, Giovanni, 1999. "An operations research model for the evaluation of an airport terminal: SLAM (simple landside aggregate model)," Journal of Air Transport Management, Elsevier, vol. 5(3), pages 161-175.
    • Handle: RePEc:eee:jaitra:v:5:y:1999:i:3:p:161-175
    DOI: 10.1016/S0969-6997(99)00010-1
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    References listed on IDEAS

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    1. Odoni, Amedeo R. & de Neufville, Richard, 1992. "Passenger terminal design," Transportation Research Part A: Policy and Practice, Elsevier, vol. 26(1), pages 27-35, January.
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    Cited by:

    1. Chaug-Ing Hsu & Ching-Cheng Chao & Nai-Wen Hsu, 2015. "Control strategies for departure process delays at airport passenger terminals," Transportation Planning and Technology, Taylor & Francis Journals, vol. 38(2), pages 214-237, March.
    2. Kim, Tae Hyun & Wu, Cheng-Lung & Koo, Tae-Ryang, 2017. "Implications of the ageing society and internationalisation for airport services: A perspective on passenger demand for personal space at airport terminals," Journal of Air Transport Management, Elsevier, vol. 60(C), pages 84-92.
    3. Castelli, Lorenzo & Pellegrini, Paola, 2011. "An AHP analysis of air traffic management with target windows," Journal of Air Transport Management, Elsevier, vol. 17(2), pages 68-73.
    4. Lalita, T.R. & Manna, D.K. & Murthy, G.S.R., 2020. "Mathematical formulations for large scale check-in counter allocation problem," Journal of Air Transport Management, Elsevier, vol. 85(C).
    5. Wu, Paul Pao-Yen & Mengersen, Kerrie, 2013. "A review of models and model usage scenarios for an airport complex system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 47(C), pages 124-140.
    6. Pitchforth, Jegar & Wu, Paul & Fookes, Clinton & Mengersen, Kerrie, 2015. "Processing passengers efficiently: An analysis of airport processing times for international passengers," Journal of Air Transport Management, Elsevier, vol. 49(C), pages 35-45.
    7. Thampan, Aromal & Sinha, Kapil & Gurjar, B.R. & Rajasekar, E., 2020. "Functional efficiency in airport terminals: A review on Overall and Stratified Service Quality," Journal of Air Transport Management, Elsevier, vol. 87(C).
    8. Giovanna Miceli Ronzani Borille & Anderson Ribeiro Correia, 2013. "Determining factors in airport baggage claim level of service," International Journal of Aviation Management, Inderscience Enterprises Ltd, vol. 2(1/2), pages 66-79.
    9. Turvey, R., 2000. "Infrastructure access pricing and lumpy investments," Utilities Policy, Elsevier, vol. 9(4), pages 207-218, December.
    10. Rodríguez-Sanz, à lvaro & Fernández de Marcos, Alberto & Pérez-Castán, Javier A. & Comendador, Fernando Gómez & Arnaldo Valdés, Rosa & París Loreiro, à ngel, 2021. "Queue behavioural patterns for passengers at airport terminals: A machine learning approach," Journal of Air Transport Management, Elsevier, vol. 90(C).
    11. Zhou, Xuemei & Huang, Huang & Jia, Xinchang & Jiang, Nan, 2014. "Integrated passenger terminal capacity analysis under the capacity constraints of surrounding road network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 194-203.

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