A case study based on a real-life production environment for the scheduling
of automated guided vehicles (AGVs) is presented. A linear programming
model is formulated for scheduling AGVs with given paths and task assign-
ments. Using the new model, a moderate size instance of 15 AGVs (all using
the same main lane connecting most of the crucial parts of the factory) can
be solved approximately with a CPLEX solver in seconds. The model is also
solved with a state-of-the art hybrid quantum-classical solver of the noisy
intermediate size quantum (NISQ) devices’ era (D-Wave BQM and CQM).
It is found that it performs similarly to CPLEX, thereby demonstrating the
“quantum readiness” of the model. The hybrid solver reports non-zero quan-
tum processing times, hence, its quantum part contributes to the solution
efficiency.