遗传算法在柔性动态调度中的应用

Genetic Algorithms Application in Flexible Dynamic Scheduling

采用一种实用的柔性制造系统 (FMS)在线动态调度方案 ,以对车间生产环境的变化作出及时反应 .建立了零件的可变工艺路径、包含 AGV的 FMS调度问题的模型 ,采用遗传算法 (GA)以任意始点的任务集为背景同时调度机器和自动引导小车 (AGV) .研究由若干台加工中心 (WS)和 AGV组成的 FMS的调度问题 .论述了综合事件机制及时间机制优点的动态调度机制 ,通过被修订的工序集与所有剩余工序形成交集 ,来识别需要被修订的工序集 .这种重调度方式减少了人为的干预 ,允许按环境改变而对方案作出修订 ,因此可以在实时条件下工作 .

An on-line scheduling/rescheduling scheme to respond timely to the dynamic changes of the environment of flexible manufacturing system (FMS) was introduced. The concerned FMS is composed of several work-stations and some automated guided vehicles (AGVs). A dynamic scheduling mechanics integrating the advantages of two commonly-used dynamic scheduling methods, named event-based and time-based, was developed. The updated task list could be formed by the conjunctive set of necessary-revised operations and remaining operations. This method could reduce the superfluous manual intervention and permit necessary revision caused by the change of environment. Simultaneously, a scheduling model with consideration of alternative routes and AGVs was set up. A GA-based method was used for scheduling machines and AGVs simultaneously. An example was calculated. The results show satisfactory performance.