It is well-recognized that Air Cargo revenue management is quite different from its passenger airline counterpart. Inherent demand volatility due to short booking horizon and lumpy shipments, multi-dimensionality and uncertainty of capacity as well as the flexibility in routing are a few of the challenges to be handled for Air Cargo revenue management. In this paper, we present a data-driven revenue management approach which is well-designed to handle the challenges associated with Air Cargo industry. We present findings from simulations tailored to Air Cargo setting and compare different scenarios for handling of weight and volume bid prices. Our results show that running our algorithm independently to generate weight and volume bid prices and summing the weight and volume bid prices into price optimization works the best by outperforming other strategies with more than 3% revenue gap.

The 16th China Air Cargo Summit, held from Nov 12-14 in Hangzhou, deliberated on the trade slowdown, its impact on air cargo and most significantly, the opportunities e-commerce is creating for the industry. "Coming after just a couple of days after 11-11 (Singles Day in China), the figures show a 23-25 percent increase over the previous years demonstrates that e-commerce is one of the significant opportunities for air cargo. Not just for the next 2-20 years, but I think it will be a long-term significant trend in the way consumerism operates," said Glyn Hughes, global head of cargo, IATA during his address. Calling the industry to respond to the strategies of the e-commerce companies with agile and flexible solutions, Hughes further added, "Regardless of the strategies employed by the e-commerce companies, data is actually critical to enable those efficiencies." "There are two main challenges – technological and regulatory. The technological challenge is, without getting into details, small drones tend to use electric power, which means they rely on lithium batteries. The other disadvantage of lithium batteries is that they are very, very heavy. This severely restricts the range of operations. With small drones, you end up with a machine that weighs 20 kilogrammes and can carry one kilogramme. The economics are not very [good]. You have some companies implementing them, especially here in China. The adoption [of drones] hasn't been big because of that. When new technologies for batteries emerge and change that equation, it would dramatically change the landscape. About the other problem is regulation, and luckily we are seeing more and more regulators around the world, including here in China. They are proactive and create drone corridors, first for testing and eventually for licensing and operations. To this day there are no consistent cargo operations drones in the world. I see that changing in the next few years though," elaborated Rangelov.

Artificial intelligence (AI) has long been touted as the transformative technology that will usher in the next generation of the logistics industry. While AI is already established in consumer tech, demonstrated by the plethora of virtual assistants, just how does AI work and how might it benefit the airfreight industry? AI simulates the human intelligence process by using complex algorithms and computer systems to acquire information, reach conclusions and solve problems. To make this work, AI requires building block technologies including big data and analytics and the internet of things which have all become highly technical and specialised technologies in their own right. For logistics to work most efficiently, the entire supply chain needs to generate a rich stream of data which can then be collected, analysed and used to optimise productivity.

The problem of efficiently packing items into containers is of great importance in the air cargo industry. Hence, the algorithms used to solve the corresponding problem should also be efficient, including their configurations. We present an algorithm configuration scenario using a state-of-the-art algorithm from this area.