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Optimal assignment for check-in counters based on passenger arrival behaviour at an airport

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  • Yonghwa Park
  • Seung B. Ahn

Abstract

Establishing how to utilize check-in counters at airport passenger terminals efficiently is a major concern facing airport operators and airlines. Inadequate terminal capacity and the inefficient utilization of facilities such as check-in counters are major factors causing congestion and delays at airport passenger terminals. However, such delays and congestion can be reduced by increasing the efficiency of check-in counter operations, based on an understanding of passengers' airport access behaviour. This paper presents an assignment model for check-in counter operations, based on passengers' airport arrival patterns. In setting up the model, passenger surveys are used to determine when passengers arrive at the airport terminals relative to their flight departure times. The model then uses passenger arrival distribution patterns to calculate the most appropriate number of check-in counters and the duration of time that each counter should be operated. This assignment model has been applied at the Seoul Gimpo International Airport in Korea. The model provides not only a practical system for the efficient operations of time-to-time check-in counter assignments, but also a valuable means of developing effective longer-term solutions to the problem of passenger terminal congestion and delays. It also offers airlines a means of operating check-in counters with greater cost effectiveness, thus leading to enhanced customer service.

Suggested Citation

  • Yonghwa Park & Seung B. Ahn, 2003. "Optimal assignment for check-in counters based on passenger arrival behaviour at an airport," Transportation Planning and Technology, Taylor & Francis Journals, vol. 26(5), pages 397-416, October.
    • Handle: RePEc:taf:transp:v:26:y:2003:i:5:p:397-416
    DOI: 10.1080/03081060310001635887
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    Cited by:

    1. Sultan Alodhaibi & Robert L. Burdett & Prasad K.D.V. Yarlagadda, 2020. "A Framework for Sharing Staff between Outbound and Inbound Airport Processes," Mathematics, MDPI, vol. 8(6), pages 1-18, June.
    2. Mujica Mota, Miguel, 2015. "Check-in allocation improvements through the use of a simulation–optimization approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 320-335.
    3. de Lange, Robert & Samoilovich, Ilya & van der Rhee, Bo, 2013. "Virtual queuing at airport security lanes," European Journal of Operational Research, Elsevier, vol. 225(1), pages 153-165.
    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. Ying Liu & Xiuqing Yang & Yong Xiang & Yi Chen & Gang Mao & Xinzhi Zhou, 2022. "Allocation and optimization of shared self-service check-in system based on integer programming model," Journal of Combinatorial Optimization, Springer, vol. 44(1), pages 532-556, August.
    6. Kim, Wonkyu & Park, Yonghwa & Jong Kim, Byung, 2004. "Estimating hourly variations in passenger volume at airports using dwelling time distributions," Journal of Air Transport Management, Elsevier, vol. 10(6), pages 395-400.
    7. Afaq Khattak & Hamad Almujibah & Feng Chen & Hussain S. Alyami, 2022. "Modified State-Dependent Queuing Model for the Capacity Analysis of Metro Rail Transit Station Corridor during COVID-19," Sustainability, MDPI, vol. 14(21), pages 1-14, October.
    8. Khattak, Afaq & Hussain, Arshad, 2021. "Hybrid DES-PSO framework for the design of commuters’ circulation space at multimodal transport interchange," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 180(C), pages 205-229.
    9. Mahmut Parlar & Moosa Sharafali, 2008. "Dynamic Allocation of Airline Check-In Counters: A Queueing Optimization Approach," Management Science, INFORMS, vol. 54(8), pages 1410-1424, August.
    10. Ornek, M. Arslan & Ozturk, Cemalettin & Sugut, Ipek, 2019. "Model-based heuristic for counter assignment problem with operational constrains: A case study," Journal of Air Transport Management, Elsevier, vol. 77(C), pages 57-64.

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