Real-Time Hybrid Flow Shop Scheduling Approach in Smart Manufacturing Environment

Smart manufacturing in the “Industry 4.0” strategy promotes deep integration of and information technologies, which makes system a ubiquitous environment. However, real-time scheduling such is challenge faced by many decision makers. To deal with this challenge, study focuses on hybrid flow shop problem (HFSP). First, characteristic smart environment analyzed, its described. Second, approach for HFSP proposed. The core module to employ gene expression programming construct new efficient rule according realtime status shop. With rule, priorities waiting job are calculated, highest priority will be scheduled at time point. A group experiments performed prove performance proposed approach. numerical show that outperforms other single-scheduling rules back-propagation neural network method optimizing most objectives different size instances. Therefore, contribution proposal approach, an effective