An Optimisation and Forecasting Framework for ULD Packing in the Air Cargo Supply Chain

An Optimisation and Forecasting Framework for ULD Packing in the Air Cargo Supply Chain

Koch, Mike (TU Delft Aerospace Engineering)

Bombelli, A. (mentor)
Santos, Bruno F. (mentor)

Delft University of Technology

Aerospace Engineering

2019-02-12

The air cargo industry is a challenging environment due to the high competition between the stakeholders involved. This demands, as example, high efficiency from cargo airlines. Efficiency can be ensured by designing loading strategies that fully exploit the available cargo volume. Unknowns in the booking dimensions and flight information make this task challenging. We propose an optimisation and forecasting framework for ULD packing. Goal of the framework is to assist analysts with their decision-making, when assessing whether a new booking should be accepted or declined. Unknown booking dimensions and flight details are forecasted using an ensemble learning method. This information is used as input for a bin packing heuristic, which assesses if the booking fits in the aircraft. In addition, we propose a risk index that quantifies what are the chances the proposed loading configuration (per ULD) is not feasible due to a mismatch between predicted and real booking dimensions.

Air Cargo
Optimisation
Forecasting
Machine Learning
ULD Packing
Loading Strategy
Shipment Dimension Forecast
Mixed Integer Linear Programming

http://resolver.tudelft.nl/uuid:60299c9f-d48e-4d84-a146-fe1b6d77806f

Student theses

master thesis

© 2019 Mike Koch