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Modeling the airline hub location and optimal market problems with continuous approximation techniques

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  • Saberi, Meead
  • Mahmassani, Hani S.

Abstract

This paper presents continuous approximation techniques for the airline hub location and optimal market problems, and illustrates the usefulness of continuous approximation modeling in airline operations and network design with example applications. The continuous approximation models are developed for airline operations in restricted and unrestricted single-hub systems. The models can support strategic planning of many-to-many airline distribution systems. Using the proposed models, the effects of changing domestic air travel demand in the United States over the years on optimal hub location are evaluated. Different levels of indifference areas of the optimal hub location are also analyzed in order to investigate the sensitivity of the studied logistic problem to the hub location. It is found that none of the existing major airline hubs fall within the 5% indifference area. However, the 10% indifference areas include Chicago, Atlanta, and Dallas, homes to United, Delta, and American Airlines, respectively. The impact of a competitive airline network structure with regard to the hub location is also studied. This study addresses a gap in the airline service planning literature on modeling the optimal market for an airline in a competitive structure with multiple airlines and already located hubs. Results from the continuous model can also provide guidelines for constructing solutions to the more detailed, but computationally heavy discrete design models.

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  • Saberi, Meead & Mahmassani, Hani S., 2013. "Modeling the airline hub location and optimal market problems with continuous approximation techniques," Journal of Transport Geography, Elsevier, vol. 30(C), pages 68-76.
    • Handle: RePEc:eee:jotrge:v:30:y:2013:i:c:p:68-76
    DOI: 10.1016/j.jtrangeo.2013.01.009
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    Cited by:

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    2. Y Bouchery & Jan C Fransoo, 2015. "Cost, carbon emissions and modal shift in intermodal network design decisions," Post-Print hal-01954452, HAL.
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    4. Ansari, Sina & Başdere, Mehmet & Li, Xiaopeng & Ouyang, Yanfeng & Smilowitz, Karen, 2018. "Advancements in continuous approximation models for logistics and transportation systems: 1996–2016," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 229-252.
    5. Alibeyg, Armaghan & Contreras, Ivan & Fernández, Elena, 2018. "Exact solution of hub network design problems with profits," European Journal of Operational Research, Elsevier, vol. 266(1), pages 57-71.
    6. Yu, Shunan & Yang, Zhongzhen & Yu, Bin, 2017. "Air express network design based on express path choices – Chinese case study," Journal of Air Transport Management, Elsevier, vol. 61(C), pages 73-80.
    7. Mohammadian, Iman & Abareshi, Ahmad & Abbasi, Babak & Goh, Mark, 2019. "Airline capacity decisions under supply-demand equilibrium of Australia’s domestic aviation market," Transportation Research Part A: Policy and Practice, Elsevier, vol. 119(C), pages 108-121.
    8. Seda Hatipoğlu & Hazal Ergül & Ecem Yazıcı, 2024. "Selection of Secondary Hub Airport Location Based on Connectivity and Green Airport Solutions," Networks and Spatial Economics, Springer, vol. 24(2), pages 507-529, June.
    9. Archetti, Claudia & Peirano, Lorenzo & Speranza, M. Grazia, 2022. "Optimization in multimodal freight transportation problems: A Survey," European Journal of Operational Research, Elsevier, vol. 299(1), pages 1-20.

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