文献类型：期刊文献

英文题名：Dynamic scheduling using immune genetic algorithm for agile mes

作者：Li, Shuxia[1]; Cao, Huan[1]; Shan, Hongbo[2]

机构：[1] East China University of Science and Technology, Meilong Rd. No130, Shanghai 200237, China; [2] Donghua University, College of Mechanical Engineering, Shanghai 200051, China

年份：2012

卷号：566

起止页码：494

外文期刊名：Advanced Materials Research

收录：EI(收录号：20124715701480)

语种：英文

外文关键词：Scheduling algorithms - Floors - Job shop scheduling - Manufacture

摘要：As a bridge links the upper enterprise planning system and the lower shop floor control system, enormous real-time information interact in shop floor, which poses great difficulty for scheduling of manufacturing execution system(MES). To meet the requirement of MES agility in the volatile information environment, dynamic scheduling becomes one of most widely used methods. In this paper, a modified immune genetic algorithm which incorporates artificial immune mechanism into genetic algorithm is presented to solve dynamic job shop scheduling problems. Owing to its good solving capability and computing speed, the algorithm could utilize real-time production information to generate predictive and reactive scheduling solutions. At last, the algorithm is applied in a MT10×10 job shop proved to be effective in obtaining better solutions than traditional genetic algorithm. ? (2012) Trans Tech Publications, Switzerland.