摘要
运用无线射频技术来实现对制造单元加工现场实时生产信息的动态获取,并针对制造单元生产过程中常发生的新任务加入、设备损坏和交货期更改的不确定性事件,以制造任务最短完工时间为调度目标,建立了单元制造任务的动态调度模型,通过引入爬山搜索方法构建了混合遗传算法,实现了对该模型的有效解算.混合遗传算法的进化操作由选择、交叉、变异与爬山进化算子组成,可有效地提高算法的收敛速度,在开发的采用实时生产信息的单元制造任务动态调度系统上进行了调度案例验证,结果表明,所提出的方法可以有效地解决不确定性事件的单元制造任务的动态调度问题,从而提高了调度方案与制造单元实际生产需求的一致性.
A dynamic job scheduling method is proposed, where radio frequency identification technology is adopted to collect the real-time production information related to workpieces, operations and facilities produced at the manufacturing spots; on the basis, to deal with the three types of uncertain events including new jobs arrival, facility breakdown and delivery-time change occurred in the manufacturing cell production, taking the shortest finishing time of jobs as the scheduling objective, a dynamic job scheduling mathematical model is established and solved with hybrid genetic algorithm designed by introducing hill-climbing searching method. Four evolution operators consisting of selection, crossover, mutation and hill-climbing are designed to effectively improve the convergence speed of the algorithm. A prototype system of dynamic job scheduling based on real-time production information is developed. The job scheduling case study is carried out and the results show that the proposed job scheduling method enables to deal with the dynamic job scheduling problems for uncertain events efficiently to improve the consistency between scheduling solutions and practical requirements of manufacturing cell production.
出处
《西安交通大学学报》
EI
CAS
CSCD
北大核心
2009年第11期56-60,共5页
Journal of Xi'an Jiaotong University
基金
国家自然科学基金资助项目(50605050
50805116)
西安交通大学机械制造系统工程国家重点实验室开发基金资助项目
关键词
任务调度
无线射频
不确定性事件
混合遗传算法
job scheduling
radio frequency identification
uncertain events
hybrid genetic algorithm