Bi-objective Flexible Job Shop Scheduling with Operation Overlapping Costs

Industry 4.0 brings a more flexible machine scheduling mode via intelligent manufacturing technologies. When each job consists of more than one operation, it may break the traditional constraint that the processing time segments of consecutive operations for a same job cannot overlap. This works studies a flexible job shop scheduling problem where consecutive operations of any job is allowed to be overlapped during processing, while the overlapping induces an extra processing cost. We establish a bi-objective mathematical model for the considered problem, aiming at the minimum makespan and the processing cost induced by the overlapping. We apply the Epsilon-constraint method to solve the model and produce the Pareto front. A brief framework of future research is provided as well. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.