A combined forecasting and packing model for air cargo loading: A risk-averse framework
In this paper, the authors 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. The authors 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. The authors 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, the authors' 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.
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- Record URL:
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/13665545
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Supplemental Notes:
- © 2022 Iordanis Tseremoglou et al. Published by Elsevier Ltd. Abstract reprinted with permission of Elsevier.
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Authors:
- Tseremoglou, Iordanis
- Bombelli, Alessandro
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0000-0001-7889-9552
- Santos, Bruno F
- Publication Date: 2022-2
Language
- English
Media Info
- Media Type: Web
- Features: Figures; References; Tables;
- Pagination: 102579
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Serial:
- Transportation Research Part E: Logistics and Transportation Review
- Volume: 158
- Issue Number: 0
- Publisher: Elsevier
- ISSN: 1366-5545
- Serial URL: http://www.sciencedirect.com/science/journal/13665545
Subject/Index Terms
- TRT Terms: Air cargo; Cargo handling; Decision support systems; Forecasting; Risk management
- Subject Areas: Aviation; Freight Transportation; Planning and Forecasting;
Filing Info
- Accession Number: 01843421
- Record Type: Publication
- Files: TRIS
- Created Date: Apr 25 2022 10:06AM