摘要
在可移动货架式仓库中发展了一种基于物流机器人的拣选系统,适应多批次、小批量、多种类分拣需求,在该系统中货位分配、拣选订单的优化组合、搬运货架的优化、AGV调度等都会影响其拣选的效率。文章针对货架搬运的优化问题,建立了数学模型,设计了求解模型的混合智能算法,并以数值算例验证了算法的有效性,对参数取值范围进行了分析,同时与启发式算法、遗传算法在优化精度、运算时间进行了对比,验证了算法稳定、高效。
The"rack to picker"picking system-Kiva,can meet the needs of multi batch,small batch and multi type sorting.However for this kind of picking system,the efficiency of picking is affected by many factors such as the location allocation,optimal combination of picking orders,optimization of handling racks,and AGV scheduling.In this paper,a mathematical model is established for the optimization of handling racks,and a hybrid intelligent algorithm is designed to solve the model.The validity of the algorithm is verified by a numerical example,and the range of parameters is analyzed.At the same time,Compared with heuristic algorithm and genetic algorithm in optimization accuracy and operation time,the hybrid intelligent algorithm is proved to be stable and efficient.
作者
姚文斌
宫改云
YAO Wenbin;GONG Gaiyun(Zhejiang Technical Institute of Economics,Hangzou 310028,China;Hangzhou Dianzi University,Hangzhou 310018,China)
出处
《物流科技》
2026年第7期31-37,共7页
Logistics Sci Tech
基金
浙江经济职业技术学院重点科研项目“货到人拣选系统中任务优化问题的研究”(X2023034)。
关键词
机器人
货架搬运优化
货到人
混合智能算法
logistics robot
shelf handling optimization
rack to picker
hybrid intelligent algorithm
