钢铁生产智能调度系统模型重构的研究
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摘要
为了满足钢铁企业实时的动态调度需求,分析了钢铁调度模型特点及规律,提出模块化的处理方式对钢铁调度模型进行划分,并提出基于集合的方法解决了钢铁调度模型单一、针对性弱的问题。重点研究了模型与集合的映射关系以及模型的重构算法,并给出了模型重构算法流程图,以实现多个模型的交、并、差运算,从而构建综合多个模型优势的新模型,满足钢铁生产智能调度的需要,避免了重复建模。最后通过两个钢铁热轧调度模型重构实例说明了模型重构的可行性。
In order to meet the needs of the real-time dynamic scheduling of iron and steel enterprises,the characters and rules of the iron and steel scheduling model are analyzed,and modular division processing method is proposed,this paper deals with an approach to solve the problem of the single and weakness steel scheduling mode based on set. The paper focus on the reconstruction algorithm and the mapping relationship between the model and set, and flow chart of model reconstruction algorithm is given,in order to achieve the set operation of multiple models with intersection, union and minus,building a new and comprehensive advantaged models to meet the needs of iron and steel intelligent scheduling,avoiding duplication of modeling. Finally,the feasibility of the model reconstruction is illustrated by two examples of hot rolling scheduling model,the proposed approach proves to be very effective.
In order to meet the needs of the real-time dynamic scheduling of iron and steel enterprises,the characters and rules of the iron and steel scheduling model are analyzed,and modular division processing method is proposed,this paper deals with an approach to solve the problem of the single and weakness steel scheduling mode based on set. The paper focus on the reconstruction algorithm and the mapping relationship between the model and set, and flow chart of model reconstruction algorithm is given,in order to achieve the set operation of multiple models with intersection, union and minus,building a new and comprehensive advantaged models to meet the needs of iron and steel intelligent scheduling,avoiding duplication of modeling. Finally,the feasibility of the model reconstruction is illustrated by two examples of hot rolling scheduling model,the proposed approach proves to be very effective.
引文
[1]蒋国璋,孔建益,李公法.基于遗传算法的钢铁产品生产计划模型研究[J].机械设计与制造,2007(5):204-206.(Jiang Guo-zhang,Kong Jian-yi,Li Gong-fa.The study of iron and steel production planning model based on genetic algorithm[J].Mechinery Design and Manufacture,2007(5):204-206.)
[2]蒋国璋,孔建益,李公法.基于B/S和ASP的连铸-连轧生产知识网系统设计研究[J].机械设计与制造,2007(3):59-61.(Jiang Guo-zhang,Kong Jian-yi,Li Gong-fa.The Study and design of continuous casting and rolling production knowledge network system based on B/S and ASP[J].Mechinery Design and Manufacture,2007(3):59-61.)
[3]高筱芸,严洪森,路致远.基于模型重构的生产计划优化系统设计与开发[J].计算机技术与发展,2006,16(3):167-169.(Gao Xiao-yun,Yan Hong-sen,Lu Zhi-yuan.The design and development of production planning optimization system based on model reconstruction[J].Computer Technology and Development,2006,16(3):167-169.)
[4]薛朝改,严洪森.基于agent网的知识网的自重构研究[J].计算机集成制造系统,2003,9(11):995-1000.(Xue Chao-gai,Yan Hong-sen.The study of knowledge network selfconstruction based on agent net[J].Computer Integrated Manufacturing System,2003,9(11):995-1000.)
[5]Xue Chao-gai,Yan Hong-sen.A study on self-reconfiguration of a knowledgeable manufacturing system[J].Mechanical Engineers,2004(218):1601-1617.
[6]Rossitza-M Setchi,Nikola Lagos.Reconfigurability and reconfigurable manufacturing systems-state of the art review[J].Electronics Engineers Computer Society,2004(46):529-535.
[7]Yan Hong-sen,Xue Chao-gai.Automatic construction and optimization of knowledge mesh for self-reconfiguration of knowledgeable manufacturing system[J].Expert System with Applications,2012(39):1799-1810.
[8]罗振璧,于学军,刘阶萍.可重构性和可重构设计理论[J].清华大学学报,2004,44(5):577-580.(Luo Zhen-bi,Yu Xue-jun,Liu Jie-ping.Reconstruction property and reconstruction design theory[J].Journal of Tsinghua University,2004,44(5):577-580.)
[9]贾佳,潘莉,屠乃威.热轧批量计划多目标智能优化编制新方法[J].控制工程,2008,15(2):220-224.(Jia Jia,Pan Li,Tu Nai-wei.A new method for multi objective optimization of hot rolling batch planning[J].Control Engineering,2008,15(2):220-224.)
[10]贾树晋,李维刚,杜斌.热轧轧制计划的多目标优化模型及算法[J].武汉科技大学学报,2015,38(1):16-22..(Jia Shu-jin,Li Wei-gang,Du Bin.The multi objective optimization model and algorithm for hot rolling plan[J].Journal of Wuhan University of Science and Technology,2015,38(1):16-22.)
[2]蒋国璋,孔建益,李公法.基于B/S和ASP的连铸-连轧生产知识网系统设计研究[J].机械设计与制造,2007(3):59-61.(Jiang Guo-zhang,Kong Jian-yi,Li Gong-fa.The Study and design of continuous casting and rolling production knowledge network system based on B/S and ASP[J].Mechinery Design and Manufacture,2007(3):59-61.)
[3]高筱芸,严洪森,路致远.基于模型重构的生产计划优化系统设计与开发[J].计算机技术与发展,2006,16(3):167-169.(Gao Xiao-yun,Yan Hong-sen,Lu Zhi-yuan.The design and development of production planning optimization system based on model reconstruction[J].Computer Technology and Development,2006,16(3):167-169.)
[4]薛朝改,严洪森.基于agent网的知识网的自重构研究[J].计算机集成制造系统,2003,9(11):995-1000.(Xue Chao-gai,Yan Hong-sen.The study of knowledge network selfconstruction based on agent net[J].Computer Integrated Manufacturing System,2003,9(11):995-1000.)
[5]Xue Chao-gai,Yan Hong-sen.A study on self-reconfiguration of a knowledgeable manufacturing system[J].Mechanical Engineers,2004(218):1601-1617.
[6]Rossitza-M Setchi,Nikola Lagos.Reconfigurability and reconfigurable manufacturing systems-state of the art review[J].Electronics Engineers Computer Society,2004(46):529-535.
[7]Yan Hong-sen,Xue Chao-gai.Automatic construction and optimization of knowledge mesh for self-reconfiguration of knowledgeable manufacturing system[J].Expert System with Applications,2012(39):1799-1810.
[8]罗振璧,于学军,刘阶萍.可重构性和可重构设计理论[J].清华大学学报,2004,44(5):577-580.(Luo Zhen-bi,Yu Xue-jun,Liu Jie-ping.Reconstruction property and reconstruction design theory[J].Journal of Tsinghua University,2004,44(5):577-580.)
[9]贾佳,潘莉,屠乃威.热轧批量计划多目标智能优化编制新方法[J].控制工程,2008,15(2):220-224.(Jia Jia,Pan Li,Tu Nai-wei.A new method for multi objective optimization of hot rolling batch planning[J].Control Engineering,2008,15(2):220-224.)
[10]贾树晋,李维刚,杜斌.热轧轧制计划的多目标优化模型及算法[J].武汉科技大学学报,2015,38(1):16-22..(Jia Shu-jin,Li Wei-gang,Du Bin.The multi objective optimization model and algorithm for hot rolling plan[J].Journal of Wuhan University of Science and Technology,2015,38(1):16-22.)