Practical approach to flexible job shop scheduling with tool switching constraints using quantum annealing

Behind production scheduling lies a trade-off between the comprehensive modeling of production system constraints and quick schedule provision. To realize mass customization, this trade-off must be addressed, requiring a model comprehensive enough for the automation of high-mix production yet quick in adapting to the dynamics of the production system. In this context, we propose a practical approach in which Flexible Job Shop Scheduling with Tool Switching Constraints, offering a model capable of representing a wide range of high-mix productions and Quantum Annealing are combined. The resulting schedules are demonstrated to be competitive, in terms of quality and computation time, are superior when compared with those obtained using Dispatching rules or Python MIP, respectively.