自动化钢板料库桥吊作业路径优化研究  

Research on route optimization of bridge crane in automated steel plate storage warehouse

作　　者：钟传捷 程文明[1,2] 杜润 ZHONG Chuanjie;CHENG Wenming;DU Run(College of Mechanical Engineering,Southwest Jiaotong University,Chengdu 610031,China;Key Laboratory of Rail Transit Operation Technology and Equipment of Sichuan Province,Chengdu 610031,China)

机构地区：[1]西南交通大学机械工程学院,成都610031 [2]轨道交通运维技术与装备四川省重点实验室,成都610031

出　　处：《现代制造工程》2023年第12期22-28,147,共8页Modern Manufacturing Engineering

基　　金：中车十四五科技重大专项科研课题项目(2021CHZ010-3);四川省重点研发项目(2022YFG0241,2022YFG0245)。

摘　　要：针对以钢板为存储对象的自动化料库中桥吊优化调度问题,对钢板料库的整体布局和桥吊出/入库作业原则等特点进行分析,提出了基于单一命令作业和复合命令作业随机组合的桥吊作业方式。以桥吊完成1批出/入库任务的总时间为评价标准,建立桥式起重机的路径优化模型。通过对遗传算法(GA)和模拟退火(SA)算法进行集成改进,并嵌入倒垛决策内层算法,设计两阶段的遗传模拟退火算法(PSAGA)对之进行求解,优化钢板的出/入库序列和桥吊最优作业路径。最后通过实例仿真,证明了PSAGA相较于传统的遗传算法具有更好的收敛性和鲁棒性,不易陷入局部最优,可以有效满足桥吊路径规划问题的需要,提高钢板的出/入库效率。Aiming at the optimization scheduling problem of bridge crane in automatic warehouse with steel plate as storage object,the overall layout of the warehouse and the operation principle of bridge crane out/in storage were analyzed,and the bridge crane operation mode based on the random combination of single operation and compound operation was proposed.The scheduling optimization model of bridge crane was established based on the total time of completing a batch of out/in storage tasks as evaluation criteria.By integrating the Genetic Algorithm(GA)and the Simulated Annealing(SA)algorithm,and embedding the shuffling stacking decision inner algorithm,a Phased Simulated Annealing Genetic Algorithm(PSAGA)was designed to solve the problem,optimize the steel plate out/in storage sequence and the optimal operation path of the bridge crane.Finally,it is proved that compared with the traditional genetic algorithm,PSAGA has better convergence and robustness,and it is not easy to fall into the local optimal.It can effectively meet the needs of the bridge crane path planning problem,and improve the steel plate out/in storage efficiency.

关 键 词：钢板料库 桥式起重机 路径优化 遗传算法 模拟退火算法 

分 类 号：TP273.5[自动化与计算机技术—检测技术与自动化装置]