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STUDY ON THE DYNAMIC SCHEDULING IN FMS REAL-TIME PRODUCTION ENVIRONMENT 被引量：2

STUDY ON THE DYNAMIC SCHEDULING IN FMS REAL-TIME PRODUCTION ENVIRONMENT
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摘要 A dynamic database based dynamic scheduling system is proposed.As the schedule is being preformed, the scheduling task data in the dynamic database is updated timely.Genetic algorithm (GA) is employed for generating optimised production plan quickly and easily in response to changes on the shop floor. The current status of the shop is considered while rescheduling, and new plan is used in conjunction with the existing schedule to improve the effeciency of flexble manufacturing systems. Simulation results demonstrate the effectiveness of the proposed system. A dynamic database based dynamic scheduling system is proposed.As the schedule is being preformed, the scheduling task data in the dynamic database is updated timely.Genetic algorithm (GA) is employed for generating optimised production plan quickly and easily in response to changes on the shop floor. The current status of the shop is considered while rescheduling, and new plan is used in conjunction with the existing schedule to improve the effeciency of flexble manufacturing systems. Simulation results demonstrate the effectiveness of the proposed system.
作者 Yang Honghong,Wu Zhiming (Department of Automation, Shanghai Jiaotong University)
出处 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2001年第3期193-197,共5页 中国机械工程学报（英文版）
基金 This project is supported by National Natural ScienceFoundation of China (No.70071017,59889505)
关键词 Dynamic scheduling Dynamic database Genetic algorithms Dynamic scheduling Dynamic database Genetic algorithms
分类号 TH165 [机械工程—机械制造及自动化]
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参考文献8

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同被引文献16

  • 1郭永辉,钱省三.基于鼓-缓冲器-绳子理论的整合式生产作业控制系统研究[J].计算机集成制造系统,2006,12(2):252-256. 被引量：10
  • 2鞠全勇,朱剑英.基于混合遗传算法的动态车间调度系统的研究[J].中国机械工程,2007,18(1):40-43. 被引量：24
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  • 5Zafar Ali. Media synchronization in multimedia Web using a neuro-fuzzy framework[J]. IEEE Journal on Selected Areas in Communication, 2000, 18(2): 168-184
  • 6Masahiko Abe. An artificial neural network optimized by a genetic algorithm for real-time Flow-shop scheduling[A]. Fonrth International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies[C]. 2000. 329-332.
  • 7Michecel J S. A neural-net approach to real time Flow-shop sequencing [J]. Computer & Industrial Engineering, 2000, 38(2) : 125- 147.
  • 8Adamopoulos G I, Pappis C P. A fuzzy-linguistic approach to a multi-criteria sequencing problem[J].European Journal of Operational Research, 1996,92(3):628-636.
  • 9Andras Bardossy. Fuzzy rule-based classification of remotely sensed imagery [J]. IEEE Transaction on Geosciences and Remote Sensing, 2002, 40(2): 362-375
  • 10CannonRL, DaveJ V, BezdekJC, et al. Segmentation of a thematic mapper image using the fuzzy cmeans clustering algorithms[J]. IEEE Transaction on Geosciences and Romote Sensing, 1986, GRS24(3) :400-408.

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Chinese Journal of Mechanical Engineering
2001年 第3期

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