粒子群算法在生产物流调度中的应用研究

Application research of particle swarm optimization in production logistics scheduling

以提高柔性制造系统(FMS)的生产效率为目标,提出了基于粒子群算法(PSO)的AGV动态调度策略。在PSO中采用三维向量的编码方式,解决了AGV资源分配与任务排序的问题,对编码后的粒子经过速度-位移计算后进行解码,通过读取数据库表得到AGV的运行时间来计算目标函数。并且提出了浮动的目标函数法,以使各AGV的任务均匀,总体最优。最后将该算法嵌入到FMS仿真实例模型中,实时进行AGV的任务调度优化,整个FMS加工任务的总完成时间较优化前缩短了12.1%,证实了算法的有效性。

Aiming at improving the productivity of Flexible Manufacturing Systems（FMS）,an AGV dynamic scheduling strategy based on the Particle Swarm Optimization（PSO） is presented.Adopting 3-D vector coding method,the problem of AGV resource allocation and task arrangement is solved in the sequence of particle encoding,velocity-displacement calculation,decoding,and the objective function is computed by reading ACCESS.The floating objective function method is presented,so every AGV task is averaged.Finally,PSO is embedded into FMS simulation model,with the AGV task arrangement optimization.In this way,the time of the FMS can be shortened by 12.1%,so the validity of the algorithm is verified.