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Logical analysis of data for estimating passenger show rates at Air Canada

Author

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  • Dupuis, Christine
  • Gamache, Michel
  • Pagé, Jean-François

Abstract

This paper examines an approach for improving the accuracy of passenger show rate predictions for airlines. The method involves the logical analysis of data. This method based on optimization techniques, detects sets of conditions for which all the satisfying passengers have a significantly higher or lower show rate than the studied population. The passengers are classified according to the patterns as show, no-show or unknown. When compared to Air Canada’s current tool for overbooking forecasts, which is based on historical statistics, logical analysis of data model appears to be very competitive.

Suggested Citation

  • Dupuis, Christine & Gamache, Michel & Pagé, Jean-François, 2012. "Logical analysis of data for estimating passenger show rates at Air Canada," Journal of Air Transport Management, Elsevier, vol. 18(1), pages 78-81.
    • Handle: RePEc:eee:jaitra:v:18:y:2012:i:1:p:78-81
    DOI: 10.1016/j.jairtraman.2011.10.004
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    Citations

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    Cited by:

    1. Travaughn C. Bain & Juan F. Avila-Herrera & Ersoy Subasi & Munevver Mine Subasi, 2020. "Logical analysis of multiclass data with relaxed patterns," Annals of Operations Research, Springer, vol. 287(1), pages 11-35, April.
    2. Guo, Xiaolong & Dong, Yufeng & Ling, Liuyi, 2016. "Customer perspective on overbooking: The failure of customers to enjoy their reserved services, accidental or intended?," Journal of Air Transport Management, Elsevier, vol. 53(C), pages 65-72.
    3. Lejeune, Miguel & Lozin, Vadim & Lozina, Irina & Ragab, Ahmed & Yacout, Soumaya, 2019. "Recent advances in the theory and practice of Logical Analysis of Data," European Journal of Operational Research, Elsevier, vol. 275(1), pages 1-15.
    4. Ahmed Ragab & Soumaya Yacout & Mohamed-Salah Ouali & Hany Osman, 2019. "Prognostics of multiple failure modes in rotating machinery using a pattern-based classifier and cumulative incidence functions," Journal of Intelligent Manufacturing, Springer, vol. 30(1), pages 255-274, January.
    5. Janostik, Radek & Konecny, Jan & Krajča, Petr, 2020. "Interface between Logical Analysis of Data and Formal Concept Analysis," European Journal of Operational Research, Elsevier, vol. 284(2), pages 792-800.
    6. Banerjee, Nilabhra & Morton, Alec & Akartunalı, Kerem, 2020. "Passenger demand forecasting in scheduled transportation," European Journal of Operational Research, Elsevier, vol. 286(3), pages 797-810.

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