混合粒子群算法在job-shop动态调度中的应用  

Application of hybrid PSO in job-shop dynamic scheduling problem

作　　者：王策[1] 王书锋[1] 冯冬青[1] 梁燕[1] 

机构地区：[1]郑州大学电气工程学院,郑州450001

出　　处：《计算机工程与应用》2010年第26期219-222,共4页Computer Engineering and Applications

基　　金：国家自然科学基金No.60774059~~

摘　　要：提出了基于事件驱动的动态调度策略,以融合遗传算法的粒子群算法来实现作业车间生产调度,有很好的收敛精度;在此基础上,对作业车间生产调度中的工件增加及取消、机器故障等各种动态事件进行了研究,能在扰动后提供新的调度计划,有效地解决了车间动态调度的一致性和连续性的问题。A new event-driven strategy of dynamic scheduling has been introduced in this paper.The particle swarm optimization which combining a genetic algorithm is used in the job shop scheduling, which has a good astringency.The dynamic events which concerning machine,job and examination have been researched in this paper and a new plan can be provided by part-renovating ,which can solve the problem of consistency and continuity in dynamic scheduling.

关 键 词：作业车间生产调度 粒子群算法 遗传算法 动态事件 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]