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。
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 Schedu- ling（DAPS） method is proposed. The optimal objective aims at the production efficiency, machine us- age rate and satisfaction degree of the due date. Then a hybrid mechanism that combines event driven with period 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.
出处
《合肥工业大学学报（自然科学版）》
CAS
CSCD
北大核心
2010年第1期5-9,共5页
Journal of Hefei University of Technology：Natural Science
基金
合肥市重点科研资助项目(070205D2)
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
dynamic advanced planning and scheduling
period driven
event driven
genetic and particle swarm optimization algorithm
