摘要
云制造环境下的供应链是新型的供应链,如何选择云制造平台中供应链节点的企业是需要解决的问题之一.针对使节点批次任务总完成时间最小的调度问题,由于蝙蝠算法容易陷入局部最优解,本文使用ROV编码对蝙蝠算法进行了重新编码和解码,并且对其进行了混沌序列初始化和自适应变步长的运算步长改进,提高了原蝙蝠算法的收敛速度和最优解的精度.通过仿真实验,结果表明改进的蝙蝠算法(IBA)较原蝙蝠算法(BA)具有更快的收敛速度、更好的稳定性,有效避免了原蝙蝠算法容易陷入局部最优解的状况,可较好地满足云制造环境下新型供应链动态性、复杂性的要求.
The supply chain under cloud manufacturing environments is a new kind supply chain in which one of the arisen problem is how to choose the node enterprises. In this paper, to solve a scheduling problem of minimizing the total completion time of a single batch task, the bat algorithm （BA） is improved by ROV coding to code and decode BA, initializing with cubic maps to give initial values and using self - adapting step widths as well, to avoid BA easily falling into local extremums and to improve its convergent rate and precision. Simulation results show that the im- proved bat algorithm （IBA） has a faster convergent rate and better stability and can solve the problem mentioned a- bove in the dynamic and complex supply chains under cloud manufacturing environments.
出处
《数学理论与应用》
2015年第2期83-94,共12页
Mathematical Theory and Applications
关键词
云制造
供应链
蝙蝠算法
时间优化
Cloud manufacturing
Supply chain
Bat algorithm
Time optimization
