计算机科学 ›› 2018, Vol. 45 ›› Issue (11A): 167-171.
岳笑含, 许晓健, 王溪波
YUE Xiao-han, XU Xiao-jian, WANG Xi-bo
摘要: 在柔性制造系统(Flexible Manufacturing System,FMS)中,自动导引小车(Automated Guided Vehicle,AGV)常被用于搬运物料或产品,因此AGV的优化调度成为提高生产效率的关键。AGV的调度除了要考虑AGV的任务分配问题,还需要参考每个操作的花费时间、小车的运行时间等因素。相比于单AGV调度算法,多AGV多任务调度算法需要一个更加复杂的模型来支撑。在考虑AGV的电量状况下,以最小完成时间与调度最少AGV数量作为优化目标,提出了一种改进的混合遗传算法与粒子群算法(PSO-GA),并基于该算法给出了多AGV调度模型,在此基础上进行了仿真实验。结果表明,相较于单一的GA或PSO算法,所提算法在全局寻优收敛与运行时间上有明显的优化效果,而相比于现有的混合PSO-GA算法,其在搜索精度和收敛速度上有进一步提高。
中图分类号:
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