遗传算法的双目标柔性作业车间调度研究

Research on bi-objective flexible job shop scheduling based on genetic algorithm

研究了FMS环境下先进制造车间路径柔性的优化调度问题.同时考虑现代生产准时制的要求,建立了柔性作业车间调度问题的双目标数学优化模型,并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网络图应用到解码和适应度函数的计算中,通过一个调度实例进行验证,给出了相应的选择、交叉、变异操作设计方案.

The flexible job-shop optimal scheduling problem in FMS is studied by analyzing the weakness of classical job-shop scheduling. Considering just-in-time production, the mathematical model of flexible job-shop scheduling（FJSS） for hi-objective is established. To solve the model, a genetic algorithm is developed. In this algorithm, a two-row chromosome structure is presented because of the special point of the model. At the same time, AOV network is applied to decode and compute the fitness function. Then selection, crossover and mutation operator of the genetic algorithm are designed. Finally, an example of job shop scheduling is shown.