基于混合遗传算法的动态车间调度系统的研究  

Study on the System of Dynamic Job Shop Scheduling Based on Combined Genetic Algorithm

作　　者：鞠全勇[1] 朱剑英[1] 

机构地区：[1]南京航空航天大学,南京210016

出　　处：《中国机械工程》2007年第1期40-43,共4页China Mechanical Engineering

基　　金：国家自然科学基金资助项目(59990470)

摘　　要：分析了生产工艺计划与车间调度系统的集成原理,提出将CAPP模块与基于周期和事件驱动的滚动窗口调度有机地相结合,从而实现工序分段设计的CAPP系统和基于周期和事件驱动的滚动窗口再调度策略的生产调度系统的集成。在建立集成模型的基础上,对算法进行研究,把简单遗传算法(SGA)和模拟退火算法(SA)有机结合,使算法优化机制融合和优化结构互补,形成高效的混合遗传算法,使集成系统能适应连续加工过程中复杂的环境变化并高效地完成实时处理,减少突发事件造成的工序大范围的重新设计。实例验证了系统的可行性和有效性。The integration principles of process planning and job shop scheduling was analyzed, which combined CAPP module with dynamic rolling windows scheduling based on period and event-driven. It has been realized that the integration of two systems. One is the CAPP system in which the procedure is designed by subsection. The other is job shop scheduling with dynamic rolling windows scheduling. Under the foundation of setting up integration module, the simple genetic algorithm was improved by combining genetic algorithm with simulated annealing. A high efficiency mixed genetic algorithm was proposed. So, the integrated system can adapt to continuous processing in a changing environment and finish the disposal in time, and reducing redesign of process planning in large scale due to outburst events. System＇s feasibility and validity was validated by an example.

关 键 词：生产调度 混合遗传算法 CAPP 集成模型 

分 类 号：U692.4[交通运输工程—港口、海岸及近海工程]