Efficient operations through cargo load optimization

If we look at the air cargo market and the data collected by IATA (International Air Transport Association), we come from a decade with a freight growth of 2.6% per year, and it is forecasted to grow by more than 4% per year.

In 2017 there were handled more than 250 billion freight tonnes per kilometer, generating 100 billion US dollars in total revenues. One of the key operational parameters is the average load factor. This is calculated as the ratio of the average load to total freight capacity in terms of kilometers. The load factor has been oscillating and it was 50% in 2017.

What about if we were able to optimize and improve the load factor? What would be the impact for each 1% we could improve? If we manage to keep the cargo yield constant, revenues can improve 1.6%. If revenues keep at the same level, we can reduce expenditures and use less gross capacity. A 1% load factor impacts in 1.6 billion in the total revenues of 2017, which were 100 billion US dollars.

So, how is it being done today? The planning is executed with a lot of restrictions, in a limited time, and optimizing using best practices, and specialized software using a limited space linear programming.

We started to address this problem last year when we participated in the Airbus Quantum Computing Challenge and took the problem of optimizing the load of containers in an aircraft. The quantum computers are well suited to address optimization problems. We have to deal with complex equations that are also applicable in the financial services domain. We are in a moment where large technology companies are competing to have the best quantum computer and bring global access to the technology. Let’s use it.

We think quantum computers will help to get a better way to plan for cargo, with the same restrictions, the same limited time, still using best practices and searching in an extended space linear programming.

Working with complex optimization problems in cargo, with the quantum computing software we aim to achieve better results than current conventional systems and help companies to improve revenues and reduce costs.

The airline cargo solution can be extended to the maritime cargo, which is a much bigger market. And the nature of equations to optimize let us enter into complex financial services problems that can be addressed with quantum computers.

We are building a piece of software that gets integrated into the legacy systems, where it is the cargo to be dispatched with a limited capacity, and we provide the best allocation based on cost and revenue restrictions.

Our core optimization algorithms are based on quantum computing technologies. Our solution brings direct financial and operational benefits. The load factor and cargo yield can be improved. And by optimizing the fleet usage according to the demand, we can reduce the asset utilization. The new optimization can help to introduce more process automation and leverage in fewer number of skilled resources.