文献类型：期刊文献

英文题名：An improved genetic algorithm for solving flexible job shop scheduling problem

作者：Zhou, Wei[1]; Bu, Yan-Ping[2]; Zhou, Ye-Qing[3]

机构：[1] School of Business, East China University of Science and Technology, Shanghai, 200237, China; [2] School of Technology, Shanghai Jiaotong University, Shanghai, 201101, China; [3] School of Mathematical Sciences, Fudan University, Shanghai, 200433, China

年份：2013

起止页码：4553

外文期刊名：2013 25th Chinese Control and Decision Conference, CCDC 2013

收录：EI(收录号：20133516668832)

语种：英文

外文关键词：Genetic algorithms - Manufacture - Computational complexity - Job shop scheduling

摘要：The Flexible Job Shop Scheduling Problem (FJSP) is a very important problem in the modern manufacturing system. It is an extension of the classical job shop scheduling problem. It allows an operation to be processed by any machine from a given set. It is also a NP-hard problem. Since FJSP requires an additional decision of machine allocation during scheduling, therefore it is much more complex problem than JSP. This paper proposed an improved genetic algorithm (IGA) to solve FJSP. We tested the IGA against the GA method. Simulation results demonstrate that it can be superior to the regular GA. We also tested the IGA with the exhaustion method to show the algorithm's efficiency. ? 2013 IEEE.