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遗传粒子群算法的动态计划与排程问题研究
引用本文:李春,葛茂根,张铭鑫,蒋增强.遗传粒子群算法的动态计划与排程问题研究[J].合肥工业大学学报(自然科学版),2010,33(1).
作者姓名:李春  葛茂根  张铭鑫  蒋增强
作者单位:合肥工业大学机械与汽车工程学院,安徽,合肥,230009
摘    要:文章针对柔性作业车间生产过程中随机出现的异常情况和频繁动态排程导致的系统振荡问题,提出了一种新的动态计划与排程方法;该方法以生产效率、设备利用率以及交货期满意程度三者综合为优化目标,采用基于事件驱动和周期驱动相结合的驱动机制,以适应生产过程中的异常情况,并提出一种改进的主、从递阶结构的遗传粒子群算法;最后,通过实例验证了该方法的有效性。

关 键 词:动态计划与排程  周期驱动  事件驱动  遗传粒子群算法

Study on dynamic advanced planning and scheduling problem based on genetic and particle swarm optimization algorithm
LI Chun,GE Mao-gen,ZHANG Ming-xin,JIANG Zeng-qiang.Study on dynamic advanced planning and scheduling problem based on genetic and particle swarm optimization algorithm[J].Journal of Hefei University of Technology(Natural Science),2010,33(1).
Authors:LI Chun  GE Mao-gen  ZHANG Ming-xin  JIANG Zeng-qiang
Abstract:In order to solve production system oscillation caused by unexpected disturbances and high frequency dynamic scheduling in the flexible job shop,a new Dynamic Advanced Planning and ScheduIing(DAPS)method is proposed.The optimal objective aims at the production efficiency,machine usage rate and satlsfaction degree of the due date.Then a hybrid mechanism that combines event driven with perod driven is developed to adapt realistic production. Finally,a hybrid algorithm-the genetic and particle swarm optimization algorithm is put forward.The hybrid algorithm is formulated in a form of master-slave hierarchical structure.The validity of the method has been proved with an example.
Keywords:dynamic advanced planning and scheduling  period driven  event driven  genetic and particle swarm optimization algorithm
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