Job shop rescheduling using a hybrid artificial immune systems and genetic algorithm model

This paper discusses on developing a hybrid model to tackle the problem of changing environment in the job shop scheduling problem. The main idea is to develop building blocks of partial schedules using the model developed that can be used to provide backup solutions when disturbances occur during production. This model hybridizes genetic algorithm (GA) with artificial immune systems (AIS) techniques to generate these partial schedules. Each partial schedule, also known as antibody, is assigned a fitness value for the selection of final population of best partial schedules. The results of the analysis are compared with previous research. Future works on this study are also discussed.