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多约束条件下生产排程智能优化技术
引用本文:周秋艳,肖满生,张龙信,张晓丽,杨文理.多约束条件下生产排程智能优化技术[J].计算机科学,2021,48(3):239-245.
作者姓名:周秋艳  肖满生  张龙信  张晓丽  杨文理
作者单位:湖南工业大学计算机学院 湖南 株洲 412007;湖南工业大学计算机学院 湖南 株洲 412007;湖南工业大学计算机学院 湖南 株洲 412007;湖南工业大学计算机学院 湖南 株洲 412007;湖南工业大学计算机学院 湖南 株洲 412007
基金项目:国家自然科学基金;湖南省自然科学基金
摘    要:针对当前企业智能化生产中,多条工艺路线共享工序以及工单在生产过程中具有多个约束条件(如工期、优先级、产量等)的问题,提出了一种以“等待时间最短”为主的生产排程智能优化算法。综合考虑工单优先级、工期长短和紧急任务插单等因素,通过一种递归算法来计算工单等待时间,以最小化工单完成时间、最大化资源利用率为优化目标,建立了多约束条件下紧急工单处理的快速响应机制。在服装加工企业中的实际应用表明,相比手工排程及其他传统算法,文中提出的优化排程算法不仅缩短了生产周期,力求各工序的负荷率最大化,使企业的生产效率提高了20%及以上,同时还改善了排程系统的稳定性。

关 键 词:生产排程  共享工序  智能优化  多约束条件

Intelligent Optimization Technology of Production Scheduling Under Multiple Constraints
ZHOU Qiu-yan,XIAO Man-sheng,ZHANG Long-xin,ZHANG Xiao-li,YANG Wen-li.Intelligent Optimization Technology of Production Scheduling Under Multiple Constraints[J].Computer Science,2021,48(3):239-245.
Authors:ZHOU Qiu-yan  XIAO Man-sheng  ZHANG Long-xin  ZHANG Xiao-li  YANG Wen-li
Affiliation:(School of Computer Science,Hunan University of Technology,Zhuzhou,Hunan 412007,China)
Abstract:Aiming at problems that multiple process routes sharing working procedures and orders in the production process have multiple constraint conditions(duration,priority,output,etc)in the current intelligent optimization production,an intelligent optimization algorithm of production scheduling based on the“shortest waiting time”is proposed.By comprehensively considering factors such as work order priority,duration,and urgent task insertion,a recursive algorithm is used to calculate the waiting time of order.Taking minimizing the completion time of work order and maximizing the utilization of resources as optimization objectives,a quick response mechanism of emergency work order processing under multi-constraint conditions is established.The practical application in garment processing enterprise shows that,compared with manual scheduling and other traditional algorithms,the optimized scheduling algorithm proposed in this paper shortens the production cycle,maximizes the load rate of each process,improves the production efficiency of enterprise by more than 20%,and improves the stability of the scheduling system.
Keywords:Production schedule  Shared process  Intelligent optimization  Multiple constraints
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