Authors: Guanghui Zhou, Mei Zheng, Zhongdong Xiao
Addresses: State Key Laboratory for Manufacturing Systems Engineering, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China. ' School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China. ' The Key Lab of Ministry of Education for Process Control and Efficiency Engineering, School of Management, Xi'an Jiaotong University, Xi'an 710049, China
Abstract: Dynamic job shop scheduling/rescheduling is a frequently occurring and highly relevant problem in practice. However, in the past, due to being short of the real-time manufacturing information derived from the bottom-level manufacturing spots, the scheduling solutions produced by the traditional job shop scheduling systems are always unable to satisfy the practical requirements well. Therefore, in this research, a dynamic job rescheduling approach is proposed in which radio frequency identification (RFID) technology is utilised to acquire the real-time manufacturing information produced at the manufacturing spots and a dynamic rescheduling mathematical model is established to deal with the four types of uncertain events frequently occurring in job shop production. Endeavouring to resolve the dynamic scheduling mathematical model effectively and efficiently, a hybrid genetic algorithm (GA) by integrating hill-climbing search method is introduced. A prototype system of RFID-based dynamic job rescheduling is developed and the numerical case studies are carried out for verifying the feasibility and validity.
Keywords: real-time data; manufacturing data; job shop rescheduling; hybrid genetic algorithms; radio frequency identification; RFID; job shop scheduling; mathematical modelling.
International Journal of Internet Manufacturing and Services, 2011 Vol.3 No.1, pp.42 - 58
Published online: 26 Mar 2011 *Full-text access for editors Access for subscribers Purchase this article Comment on this article