具有有限缓存的模具FMS单AGV调度研究

在实际生产应用FMS中,由于加工单元缓存区容量有限导致在一段时间内单AGV工件运输任务的累积,增加模具生产成本及延长模具完工时间,为了解决此问题,建立了有限缓存区容量的AGV调度模型,并根据模型特点设计了改进遗传算法求解AGV的最短路径,改进遗传算法的选择操作采用轮盘赌选择和最佳个体保存相结合的方法以保持种群的多样性。实例结果表明,与传统的遗传算法相比,改进遗传算法具有更快的收敛速度,并且得到最优解的概率更高。

Scheduling study for single AGV in FMS of die & mould with finite buffers

In FMS of die mould production, the transportation tasks of single AGV may be accumulated in a period of time due to the finite buffers of manufacturing cells, leading to the increase of die mould production costs and duration. To solve the problem, a scheduling model of single AGV was proposed and an improved genetic algorithm was developed to solve the shortest path according to the characteristics of the model. Roulette wheel selection and the best individual reserved method were combined for the selection operation to maintain the diversity of the population, and a crossover operator to raise the value of fitness was applied to improve the convergence speed. The results of experiments indicate that the proposed algorithm is more effective and performs well with higher probability to have an optimal solution than traditional algorithm.