遗传算法在柔性动态调度中的应用

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。

Genetic Algorithms Application in Flexible Dynamic Scheduling

An on line scheduling/rescheduling scheme to respond timely to the dynamic change 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 timed based, was developed. The updated task list could be formed by the conjunctive set of operations necessary to be revised and the 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.