An intelligent decision-support system for air cargo palletizing

Abstract

Palletizing in the air cargo sector faces a large number of constraints (e.g., aviation safety regulations) and represents a highly complex problem. In air cargo operations, there is hardly any digital support to optimize the palletizing process. As a result, desired objectives (e.g., optimal utilization of the possible loading weight, maximum use of the available loading space, or both) are often only met by chance. The goal of this research is to report on the design and performance of an intelligent decision support system that we built for the air cargo context. This system supports the manual palletizing process by considering far more constraints as well as more complex item shapes and unit load devices than any other system we know. We explain the problem context, including the essential requirements; model the solution design; and develop the intelligent decision support system as an artifact, which we then evaluate.