In the quest for more real-world Quantum use-cases, Cambridge Quantum (CQ) and Deutsche Bahn Netz AG (DB) announced today a partnership to explore how quantum computers can improve the rescheduling of rail traffic as part of DB’s long-term transformative plan. Classically the problem can be intensive requiring vast computational resources to crunch through all the possibilities of rosters for example. The problem set is one that is often touted as a putative use case for Quantum Computing.
CQ’s latest combinatorial optimisation algorithm Filtering Variational Quantum Eigensolver (F-VQE) coupled with DB’s operations research expertise, the team re-optimised realistic train timetables after simulated delays and are now identifying areas for continued study. This collaboration shows how innovation in both quantum algorithms and domain-specific modelling can generate a long-term vision for a faster and greener transportation network.