文献类型：会议论文

中文题名：An Improved Genetic Algorithm for Solving Flexible Job shop Scheduling Problem

作者：ZHOU Wei;BU Yan-ping;ZHOU Ye-qing

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

会议论文集：the 25th Chinese Control and Decision Conference(第25届中国控制与决策会议)论文集

会议日期：20130500

会议地点：贵阳

主办单位：中国航空学会;中国自动化学会;中国人工智能学会;中国系统仿真学会

语种：英文

中文关键词：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.