基于遗传算法的柔性作业车间调度优化

A scheduling optimization of flexible job-shop using genetic algorithm

针对经典作业车间调度问题的局限性 ,结合实际生产情况 ,提出了具有路径柔性的作业车间调度模型 ,给出了求解模型的遗传算法的具体实现过程。针对模型的特殊性 ,提出了染色体两层编码结构 ,将AOV、AOE网络图分别应用到解码和适应度函数的计算中 ,并给出了相应的选择、交叉、变异操作设计。最后通过一个 8× 6调度问题的测试例子 。

In this article we presented a model for flexible job-shop scheduling on analyzing the weakness of classical job-shop. To solve the model, a genetic algorithm was developed. In this algorithm, we presented a two-row chromosome structure because of the special point of the model . At the same time , AOV and AOE network were applied to decoding and computing the fitness function. Then we designed selection, crossover and mutation operator of the genetic algorithm. Finally, a example of 8×6 scheduling showed that the genetic algorithm was efficient.