IQM and Deutsche Bahn Demonstrate Hybrid Quantum Algorithm for Railway Scheduling on Real Operational Data
IQM Quantum Computers and Deutsche Bahn have published results of a hybrid quantum-classical algorithm applied to real railway scheduling data. The approach used the Quantum Approximate Optimization Algorithm on a dataset of 190 trips across five German cities, generating roughly 98,500 possible cycles. Feasible schedules were produced end-to-end on existing IQM hardware, with solution quality scaling alongside larger quantum subproblems. The framework is designed for generalization to logistics, energy, and manufacturing optimization problems.
July 20, 2026