Job shop rescheduling using a hybridization of genetic algorithm and artificial immune systems

• Main Authors: Mohamed Din, Aniza, Ku-Mahamud, Ku Ruhana, Yusof, Yuhanis, Mahmuddin, Massudi
• Format: Conference or Workshop Item
• Language: English
• Published: 2012
• Subjects: QA76 Computer software
• Online Access: http://repo.uum.edu.my/6974/1/P7_-_ISSC2012.pdf; http://repo.uum.edu.my/6974/; http://issc.uum.edu.my/index.php/ISSC2012/ISSC2012
• Institution: Universiti Utara Malaysia

This paper discusses on developing a hybrid model of genetic algorithm and artificial immune systems to tackle the problem of changing environment in the job shop scheduling problem. The main idea is to use the model to develop building blocks of partial schedules that can be used to provide backup solutions when disturbances occur during production.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 a previous work. Future works on this study are also discussed.