Solving flexible job shop scheduling problems in manufacturing with Quantum Annealing

Abstract Quantum Annealing (QA) is a metaheuristic for solving optimization problems in time-efficient manner. Therefore, quantum mechanical effects are used to compute and evaluate many possible solutions of an problem simultaneously. Recent studies have shown the potential QA such complex assignment within milliseconds. This also applies field job shop scheduling, where existing approaches however focus on small sizes. To assess full this area industry-scale formulations, it necessary consider larger instances potentials computing these scheduling while finding near-optimal solution Consequently, paper presents QA-based scheduling. In particular, flexible various sizes computed with QA, demonstrating efficiency approach regarding scalability, quality, time. For evaluation proposed approach, compared scientific benchmark state-of-the-art algorithms problems. The results indicate that has time efficient Even large can be seconds, which offers possibility application industry.