基于A-HGA的某钢材加工配送中心车间调度  

Based on A-HGA research JSS problem of one Steel Processing and Distribution Center

作　　者：李苗[1] 林强[1] 

机构地区：[1]天津大学管理与经济学部,天津300072

出　　处：《工业工程与管理》2010年第6期51-57,共7页Industrial Engineering and Management

基　　金：教育部人文社会科学(09YJC630165);天津大学自主创新基金社会影响力专项;国家自然科学基金资助项目(70771073)

摘　　要：针对某钢材加工配送中心生产现场存在的在制品仓过多,材料拉动的及时性差以及各机床的负荷分布不均匀等问题,通过解释结构模型找出其发生的真因并得出改善思路。为获得解决方案,将该钢卷生产调度问题抽象为一类JSS(job-shop scheduling作业车间调度)一般性模型,并设计出自适应递阶遗传算法(A-HGA)进行求解,Matlab运行结果表明,该算法的调度结果优于经验排配,提高了机床平均利用率,解决了WIP仓过多,材料拉动的及时性差等问题。同时由于该算法的编码简单、染色体信息量大、收敛性好,在解决一类复杂JSS和拓扑结构等多变量优化问题方面有明显优势。Aimed at the problems of excessive WIP,lacking timeliness in pulling materials and not uniform distribution of machines＇ load existed in production field of one steel processing and dispatching center,through ISM（interpretive structural model） this paper find the root cause and obtain the improve thought.In order to achive solutions,it describes the steel＇s production scheduling as a general Job-Shop Scheduling model,and designes an Auto-adapted Hierarchical Genetic Algorithm（A-HGA） to solve the model.The results of Matlab operation prove that A-HGA＇s scheduling is better than experience scheduling,and also improving the average utilization rate of machines,solving the problems of excessive WIP and lacking timeliness in pulling materials.Same time,as the algorithm＇s simple coding,informative chromosome and good convergence,it has obvious advantages in solving multi-variable optimization problems such as complex JSS and topology structure.

关 键 词：JobShop调度 递阶遗传算法 自适应算子 ISM解释结构模型 MATLAB 

分 类 号：F273[经济管理—企业管理]