文献类型：会议论文

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]E China Univ Sci & Technol, Sch Business, Shanghai 200237, Peoples R China;[2]Shanghai Jiao Tong Univ, Sch Technol, Shanghai 201101, Peoples R China;[3]Fudan Univ, Sch Math Sci, Shanghai 200433, Peoples R China

会议论文集：25th Chinese Control and Decision Conference (CCDC)

会议日期：MAY 25-27, 2013

会议地点：Guiyang, PEOPLES R CHINA

语种：英文

外文关键词：genetic algorithm; flexible job shop scheduling problem; multi-objective optimization; makespan

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.