摘要
以冷轧连续退火机组能耗集中的炉区作为研究对象,根据能量流与热力学理论,建立了能耗与主要工艺参数之间的映射模型;采用MATLAB结合一种改进的量子遗传算法对能效模型进行优化,获取在保证质量的前提下能效最高的工艺参数组合;以辅助设备能耗最低、生产规格跳变平缓以及满足交货期为优化目标,建立了冷轧连退产线生产调度多目标优化模型,采用非支配排序遗传算法(NSGA-Ⅱ)进行求解,得出最优排序。结果表明,该模型和算法对生产实际有一定的指导作用。
The furnace area with concentrated energy consumption of cold rolling continuous annealing units was studied.The theory of energy flow and thermodynamics was used to establish a mapping model between energy consumption and main process parameters.Combining MATLAB and an improved quantum genetic algorithm,the energy efficiency model was optimized to obtain a process parameter combinations with the highest energy efficiency under the premise of quality assurance.The minimum energy consumption of auxiliary equipment,the smooth transition of production specifications and the satisfaction of delivery time were used as optimization targets.The multi-objective optimization model of production scheduling for cold rolling continuous annealing lines was established and solved by NSGA-Ⅱ,and then the optimal sorting was presented.The results show that the model and the algorithm have a certain guiding effectiveness on production.
作者
杨杰
胡琦
肖亭
张文颖
张超勇
YANG Jie;HU Qi;XIAO Ting;ZHANG Wenying;ZHANG Chaoyong(School of Mechanical and Electronic Information,China University of Geosciences,Wuhan,430074;State Key Laboratory of Digital Manufacturing Equipment and Technology,Huazhong University of Science and Technology,Wuhan,430074)
出处
《中国机械工程》
EI
CAS
CSCD
北大核心
2020年第14期1724-1732,共9页
China Mechanical Engineering
基金
国家自然科学基金国际(地区)合作与交流项目(51561125002)
国家自然科学基金资助项目(51575211,51805330,51705263)
高等学校学科创新引智计划资助项目(B16019)。
关键词
退火机组
能效模型
量子遗传算法
调度模型
非支配排序遗传算法
annealing unit
energy efficiency model
quantum genetic algorithm
scheduling model
non-dominated sorting genetic algorithm(NSGA-Ⅱ)
