A novel dynamic scheduling strategy for solving flexible job-shop problems

A simulation model was established, minimizing the makespan and stability value, to solve the dynamic scheduling of flexible job-shop problems, and an improved hybrid multi-phase quantum particle swarm algorithm is proposed. Firstly, a double chain structure coding method, including a machine allocation chain and a process chain, is proposed. Secondly, a dynamic periodic and event-driven scheduling strategy is proposed. Finally, the novel method is applied to the Brandimarte set and a dynamic simulation is performed. Comparing the results with the results of existing algorithms demonstrates the effectiveness of the proposed hybrid multi-phase quantum particle swarm optimization algorithm and strategy for solving the dynamic scheduling of flexible job-shop problems.