Ananlysis and Scheduling for Distributed Robust Production Lines with Bernoulli Machines and Sequence-dependent Setup Time

Driven by the increasing need of enterprises to meet the demands of multi-cooperation production, the distributed flow shop scheduling problem (DFSP) has emerged as a cutting-edge research topic in the field of flexible manufacturing. Because of the uncertainties in practical production environment of the distributed production lines, the processing efficiency of machines can be undetermined in different scenarios. In this paper, a robust model for DFSP with Bernoulli machines and sequence-dependent setup time is studied. Firstly, the robust model and the analysis of distributed production lines are formulated. Secondly, an improved genetic algorithm with linear rank selection and acceptance criterion is proposed, which has been empirically proven to effectively overcome the issue of being stuck in local optima. Finally, the result of the comparative experiments shows that the proposed improved genetic algorithm can solve the distributed flow shop scheduling problem with uncertain processing efficiency (UPE) and sequence-dependent setup time.