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A combined forecasting and packing model for air cargo loading: A risk-averse framework

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  • Tseremoglou, Iordanis
  • Bombelli, Alessandro
  • Santos, Bruno F.

Abstract

In this paper, we present a combined forecasting and optimization decision-support tool to assist air cargo revenue management departments in the acceptance/rejection process of incoming cargo bookings. We consider the case of a combination airline and focus on the passenger aircraft belly capacity. The process is dynamic (bookings are received in a discrete fashion during the booking horizon) and uncertain (for some bookings the three dimensions are not provided, while the actual belly space available for cargo is only revealed a few hours before departure). Hence, analysts base decisions on historical data or human experience, which might yield sub-optimal or infeasible solutions due to the aforementioned uncertainties. We tackle them by proposing data-driven algorithms to predict available cargo space and shipment dimensions. A packing problem is solved sequentially once a new booking request is received, predicting shipment dimensions, if necessary, and considering the uncertainty of such prediction. The booking is accepted if it results in a feasible loading configuration where no previously accepted booking is offloaded. When applied in a deterministic context, our packing method outperformed the one used by the partner airline, increasing the loaded volume up to 20%. The framework was also tested assuming unknown shipment dimensions, comparing a risk-prone and a risk-averse strategy, with the latter accounting for uncertainty in dimension predictions and the former using mean values. While the average loaded volume decreases in the risk-averse case, the number of unplanned offloadings due to under-predicted dimensions decreases from 54% to 12% of the simulated cases, hence yielding a more robust acceptance strategy.

Suggested Citation

  • Tseremoglou, Iordanis & Bombelli, Alessandro & Santos, Bruno F., 2022. "A combined forecasting and packing model for air cargo loading: A risk-averse framework," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
  • Handle: RePEc:eee:transe:v:158:y:2022:i:c:s1366554521003367
    DOI: 10.1016/j.tre.2021.102579
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    References listed on IDEAS

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    1. Zhao, Xian & Wang, Xinlei & Dai, Ying & Qiu, Qingan, 2024. "Joint optimization of loading, mission abort and rescue site selection policies for UAV," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    2. Ma, Hoi-Lam & Sun, Yige & Chung, Sai-Ho & Chan, Hing Kai, 2022. "Tackling uncertainties in aircraft maintenance routing: A review of emerging technologies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).

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