基于贝叶斯公式的炼钢厂天车调度方法

Crane scheduling method in steelmaking plant based on Bayesian theory

针对炼钢厂天车任务具有时序性、冲突性和不确定性的特点,提出一种基于贝叶斯公式的天车调度方法.首先,解析炼钢厂内天车任务的产生规律,构建天车调度过程的贝叶斯网络;然后,计算各类天车任务产生的时空概率分布;最后,根据可用天车数量匹配运输任务,动态生成天车调度方案.基于天车调度仿真系统,利用某炼钢厂10900条实际的天车任务数据,对该天车调度方法测试表明,所提出方法可在规定时间内有效地完成所有天车任务;与人工调度方法相比,完成任务总时间、天车避让次数、由于天车避让导致额外的运输时间均明显减少.在提高天车运行效率的同时,减少天车碰撞的安全风险.

Aiming at crane tasks’ characteristics of sequentiality,confliction and uncertainties in steel plants,a crane scheduling method based on Bayesian theory is proposed.Firstly,the rule of generating crane tasks in steel plants is analyzed,and the Bayesian network for crane scheduling process is constructed.Then,the corresponding time-space probability distribution of crane tasks is calculated.Finally,the number of available cranes are assigned to crane tasks,and the crane scheduling plan is generated dynamically.Based on the crane scheduling simulation system,10 900 pieces of actual crane task data are applied.The testing result indicates that the crane scheduling method based on Bayesian theory can effectively complete all crane tasks within the scheduled time.Compared with manual scheduling methods,the total time to complete the task,the frequency of crane avoidance and the additional transportation time caused by crane avoidance are all dramatically reduced.While improving the operation efficiency of cranes,the security risk from crane collision is reduced.