基于遗传算法的柔性车间批量调度研究

Study on Batch Splitting Scheduling of Flexible Workshop Based on Genetic Algorithm

针对一类柔性车间批量生产问题,提出了新的调度策略:区分工件的批量准备时间和加工时间;小批次调度策略。在此基础上,采用遗传算法作全局优化算法来实现最优调度,给出了批次调度策略下的遗传算法的编码、解码方案,以及一种特殊的交叉操作设计。仿真算例分析表明,一方面,所设计的遗传算法对解决柔性调度问题具有理想的效果,另一方面,在采用相同优化算法的前提下,分批次调度策略可以缩短工件的生产周期。

New strategy for the job - shop scheduling based on batch process of Flexible workshop is put forward. Firstly, the machine＇s setup time before a job arriving is separated from the job＇s producing time. Secondly, batch -splitting method is adopted. Then the genetic algorithm is introduced to optimize the whole scheduling and choose the best one. To explain this, this topic gives design of encoding , deco- ding and a special crossover operation for genetic algorithms based on batch process. From the given example we can draw a conclusion that genetic algorithm is very effective for solving job - shop scheduling , but even the same algorithm is used, batch splitting strategy can earn a less producing time.