集团分布式制造模式下生产调配优化模型研究及算法设计
|
摘要
基于分布式概念的集团分布式制造生产管理模式在市场中占据着越来越重要的地位,此种运营模式由制造型企业向服务型企业蔓延的趋势也越来越明显,然而针对这一具有自身特点的集团分布式概念下的生产管理模型的调度研究却很少。研究针对此生产管理模式下集团级的生产调配问题建立数学模型,综合考虑客户订单的分散情况、各分厂日生产能力限制和产品品种多样性的特点,采用改进的遗传算法求解该模型,提出一种基于订单和工厂的两段式非负整数染色体编码方法,保证了生产能力约束和订单约束,采用PMX交叉算法避免不合法染色体的出现。选取W集团一定计划期内的客户订单数据进行实例分析,验证了该生产调配模型和算法的有效性。
The mode of Group Distributed Manufacturing production management based on the distributed concept has become more and more important in present market,and the trend of this operation mode changing from manufacturing enterprise to the service-oriented businesses is increasingly conspicuous.However,there exists little special scheduling research about this production management mode.Therefore,in this study a mathematical model for the production allocation problem in Group level is established,which takes the dispersion of customer orders and the limitations on factory production capacity and species diversity of production into consideration.Then,the genetic algorithm is applied to solve this problem and put forward a new two-stage and non-negative integer chromosome coding method based on the order and factory to ensure the production capacity and order constraints.The PMX cross algorithm avoids the production of illegitimate chromosome.Besides,a period of order data coming from W Group Company is analyzed to justify the validity of the model and the algorithm.
The mode of Group Distributed Manufacturing production management based on the distributed concept has become more and more important in present market,and the trend of this operation mode changing from manufacturing enterprise to the service-oriented businesses is increasingly conspicuous.However,there exists little special scheduling research about this production management mode.Therefore,in this study a mathematical model for the production allocation problem in Group level is established,which takes the dispersion of customer orders and the limitations on factory production capacity and species diversity of production into consideration.Then,the genetic algorithm is applied to solve this problem and put forward a new two-stage and non-negative integer chromosome coding method based on the order and factory to ensure the production capacity and order constraints.The PMX cross algorithm avoids the production of illegitimate chromosome.Besides,a period of order data coming from W Group Company is analyzed to justify the validity of the model and the algorithm.
引文
[1]谭伟,张根保,刘英.分布式制造环境下的集成化工艺信息系统研究[J].机床与液压,2001,4:167-168.
[2]郎志冲.集团分布式制造模式的研究[J].技术研发,2010,17(2):42-43.
[3]周金宏,汪定伟.分布式多工厂单件制造企业提前/拖期生产计划研究[J].计算机集成制造系统,2000,6(5):52-57.
[4]Zhang Ying,Wang Dingwei.Genetic algorithms for optimizing of multiple resource scheduling problem[J].Journal of Shenyang University of Technology,2002,6:212-214.
[5]周金宏,汪定伟,徐洋.软计算求解分布式多工厂多顾客的供应链准时化生产计划问题[J].控制与决策,2011,16(6):894-897.
[6]周金宏,汪定伟.分布式多工厂、多分销商的供应链生产计划模型[J].信息与控制,2001,30(2):169-172.
[7]Tatsushi Nishi,Masami Konishi,Masatoshi Ago.A distributed decision making system for integrated optimization of production scheduling and distribution for aluminum production line[J].Computer&Chemical Engineering,2007,31(10):1205-1221.
[8]Wang D.Earliness-tardiness production planning approaches for manufacturing system[J].Computer&Industrial Engineering,1995,28(3):425-436.
[9]顾学民.分布式制造环境下的作业调度研究[D].西北工业大学:西安,2005.
[10]何琨,赵勇.网格环境下资源调度问题的统一建模与分析[J].华中科技大学学报(自然科学版),2006,34(3):35-38.
[11]Di Martino V,Mililotti M.Sub optimal scheduling in a grid using genetic algorithms[J].Parallel Computing,2004,305.
[12]何锟,赵勇,陈阳.分布式环境下多任务调度问题的分析与求解[J].系统工程理论与实践,2007,(5):119-125.
[13]孔令浩.面向集团分布式制造模式的敏捷性研究[D].天津大学:天津,2012.
[14]刘洪伟,段宏亮.集团分布式制造模式下生产计划与调度研究[J].组合机床与自动化加工技术,2014,4:146-149.
[15]余建军,张定超,周铭新.生产调度研究综述[J].中国制造业信息化,2009,38(19):13-17.
[16]何锟,赵勇,陈阳.分布式环境下多任务调度问题的分析与求解[J].系统工程理论与实践,2007(5):119-125.
[17]张超勇,饶运清,李培根,等.柔性作业车间调度问题的两级遗传算法[J].机械工程学报,2007,43(4):119-124.
[18]雷英杰.MATLAB遗传算法工具箱及应用[M].西安:西安电子科技大学出版社,2005:48-51.
[19]张志涌.精通MATLAB R2011a[M].北京:北京航空航天大学出版社,2011.
[2]郎志冲.集团分布式制造模式的研究[J].技术研发,2010,17(2):42-43.
[3]周金宏,汪定伟.分布式多工厂单件制造企业提前/拖期生产计划研究[J].计算机集成制造系统,2000,6(5):52-57.
[4]Zhang Ying,Wang Dingwei.Genetic algorithms for optimizing of multiple resource scheduling problem[J].Journal of Shenyang University of Technology,2002,6:212-214.
[5]周金宏,汪定伟,徐洋.软计算求解分布式多工厂多顾客的供应链准时化生产计划问题[J].控制与决策,2011,16(6):894-897.
[6]周金宏,汪定伟.分布式多工厂、多分销商的供应链生产计划模型[J].信息与控制,2001,30(2):169-172.
[7]Tatsushi Nishi,Masami Konishi,Masatoshi Ago.A distributed decision making system for integrated optimization of production scheduling and distribution for aluminum production line[J].Computer&Chemical Engineering,2007,31(10):1205-1221.
[8]Wang D.Earliness-tardiness production planning approaches for manufacturing system[J].Computer&Industrial Engineering,1995,28(3):425-436.
[9]顾学民.分布式制造环境下的作业调度研究[D].西北工业大学:西安,2005.
[10]何琨,赵勇.网格环境下资源调度问题的统一建模与分析[J].华中科技大学学报(自然科学版),2006,34(3):35-38.
[11]Di Martino V,Mililotti M.Sub optimal scheduling in a grid using genetic algorithms[J].Parallel Computing,2004,305.
[12]何锟,赵勇,陈阳.分布式环境下多任务调度问题的分析与求解[J].系统工程理论与实践,2007,(5):119-125.
[13]孔令浩.面向集团分布式制造模式的敏捷性研究[D].天津大学:天津,2012.
[14]刘洪伟,段宏亮.集团分布式制造模式下生产计划与调度研究[J].组合机床与自动化加工技术,2014,4:146-149.
[15]余建军,张定超,周铭新.生产调度研究综述[J].中国制造业信息化,2009,38(19):13-17.
[16]何锟,赵勇,陈阳.分布式环境下多任务调度问题的分析与求解[J].系统工程理论与实践,2007(5):119-125.
[17]张超勇,饶运清,李培根,等.柔性作业车间调度问题的两级遗传算法[J].机械工程学报,2007,43(4):119-124.
[18]雷英杰.MATLAB遗传算法工具箱及应用[M].西安:西安电子科技大学出版社,2005:48-51.
[19]张志涌.精通MATLAB R2011a[M].北京:北京航空航天大学出版社,2011.