In early 2019, Airbus launched the Airbus Quantum Computing Challenge, addressing aerospace flight physics problems, to test and assess the newly available computing capabilities to solve some of the most difficult and complex problems. A team from Universidad de Montevideo worked on the problem of aircraft loading optimisation. The team created the start-up Quantum-South to thrive in the quantum computing space. On November 2020 Airbus confirmed the team as one of the finalists of the challenge.
Airbus challenge put forward five distinct flight physics problems with varying degrees of complexity, ranging from a simple mathematical question to a global flight physics problem.
The problem N°5 was stated as follows by Airbus: “Airlines try to make the best use of an aircraft’s payload capability to maximise revenue, optimise fuel burn and lower overall operating costs. Their scope for optimisation is limited by the aircraft’s operational envelope, which is determined by each mission’s maximum payload capacity, the aircraft’s centre of gravity and its fuselage shear limits. The objective of this challenge is to calculate the optimal aircraft configuration under coupled operational constraints, thus demonstrating how quantum computing can be used for practical problem solving and how it can scale towards more complex issues”.
The problem of determining the optimal loading strategy for packing merchandise in vehicles has been addressed using different techniques like dynamic or genetic programming. Inspired in the well-known Knapsack Problem, our solution aims at determining the optimal configuration of maximizing the loading of a cargo airplane -subject to constraints- using quantum algorithms.
Our approach is based on the Variational Quantum Eigensolver (VQE) algorithm. Understanding the complexity of classical computational methods, we aim to find the quantum advantage provided by the VQE in a hybrid solution.
As the number of packages to be transported grows the number of possible combinations increases posing a serious challenge to be solved by classical means.
Based on the complexity order of the problem we project the number of necessary qubits to solve it and the feasibility of running the algorithm in a quantum computer currently available or in the near future.
A multidisciplinary team was assembled to work in the project, and with weekly work during several months, finally delivered a solution at the end of October 2019. The team was integrated by Dr. Rafael Sotelo (Team Leader – Director of Information Technology and Telecommunications at Universidad de Montevideo), Dr. Gerardo Beltrame (Senior Physics Expert), Martín Machín (Team Leader), Joaquín Fernández Ojeda (Software Developer), Diego Gibert (Software Developer), Juan Diego Orihuela (Software Developer), Ignacio Méndez (Optimization Expert), José Pedro Algorta (Software Developer), Maximiliano Stock (Optimization Expert) and Laura Gatti (Quantum Computing Expert).
Airbus experts from engineering and flight physics teamed up with leading academic and industry experts in Quantum Computing to support the evaluation of submitted proposals.
The jury members selected five teams for the 2020 final: Capgemini, Machine Learning Reply, Niels Backfisch, Origin Quantum and Universidad de Montevideo.
Airbus released a special podcast with the external judges Elham Kashefi and Iordanis Kerenidis, Thierry Botter from Airbus Blue Sky and Lee-Ann Ramcherita from Airbus’ Flight Physics department explaining the assessment and the testimonies of the finalists.
The team of Universidad de Montevideo and the spin-off Quantum-South continue working on optimization problems using technology from various vendors and offering consulting to logistics and financial industries.
The team is very happy with the journey started with the Airbus Quantum Computing Challenge. The continued work let Quantum-South emerge to work with complex optimization problems for air cargo leveraging quantum computing technologies.