改进贝叶斯算法的刀具工序调度
2018-12-20
作者:李丽娟1,郭天赐1,曹岩1,刘菊花2,孙夏辉2
单位:1西安工业大学;2河南平原光电有限公司
摘要:为解决FMS(柔性制造系统)中工序流与刀具流集成优化调度问题,以生产总时间最小为优化目标,提出了一种基于改进贝叶斯算法的优化方法,构建了基于变量取值的概率描述模型——改进贝叶斯网络,以历史运行经验为最初解群,然后以所构建的模型产生新的可行解用以组成下一代解群。经测试表明:该模型与传统遗传算法和贝叶斯算法想比,刀具整体利用率和机床整体利用率9%、11%和4%、7%。
关键词:FMS;贝叶斯算法;工序流
中图分类号:TG71; TG702 ;TP181;O212文献标志码:A
Optimization of Cutter Processes Based on Bayesian Algorithm
Li Lijuan,Guo Tianci,Cao Yan,Liu Juhua,Sun Xiahui
Abstract:To solve the integration scheduling problem of process flow and tool flow in FMS (flexible manufacturing system),aiming at the objective of minimizing the total production time,an optimization method based on improved Bayesian algorithm is proposed.A probabilistic description model based on variable values is constructed,which is to improve the Bayesian network.The historical operation experience is the initial solution group,and then the new feasible solution is generated by the constructed model to form the next generation solution group.The results show that this model is better than the traditional genetic algorithm and Bayesian algorithm in that the overall tool utilization rate and overall machine tool utilization rate are 9%,11% and 4%,7%.
Keywords:FMS;Bayesian algorithm;process flow