Extension of reactive scheduling method using co-evolutionary genetic algorithms (application to open shop scheduling problems and experimental evaluation)

Unexpected disruptions, such as delays of manufacturing processes, addition of emergent jobs and failures in manufacturing equipment, often occur in the actual manufacturing systems, and a predetermined production schedule may not satisfy given constraints due to the disruptions in the manufacturing systems. This research proposed a new reactive scheduling method using the co-evolutionary genetic algorithm. The proposed method alternately modifies the loading sequences of jobs and the machining sequences of jobs in a very short time, in order to improve the disturbed production schedules without interrupting the progress of manufacturing process. A prototype of an extended reactive scheduling system is developed to evaluate the effectiveness of the proposed method. Some computational experiments are carried out for unexpected delays of manufacturing processes.