改进PSO和机器状态对车间任务调度研究

JOB SHOP SCHEDULING BASED ON IMPROVED PSO AND MACHINE STATE

针对纺织车间的多任务对应多设备生产的静态车间任务分配问题,以改进粒子群算法(PSO)对订单任务完成时间最少进行分析。以机械状态影响任务调度使车间拥有足够的时间预防突发事件。在生产效率和机械可靠性基础上设计目标函数并进行任务分配。提出柯西分逆累积分布更新粒子位置函数,进行粒子更新,实现快速收敛。通过实际案例验证整个车间任务分配过程。验证结果表明,该算法能有效优化车间资源的利用率。

Aiming at the task assignment problem in static textile workshop in which multi tasks correspond to multi device,the least completion time of order task was analyzed based on improved particle swarm optimization.And the mechanical state was used to influence the task scheduling so that the workshop had enough time to prevent emergencies.The objective function was designed and the tasks were allocated on the basis of efficiency and mechanical reliability.Cauchy distribution was proposed to update particle location function,update particles and achieve fast convergence.The whole process of task allocation was verified through real cases.The results show that the algorithm can effectively optimize the utilization rate of workshop resources.