KIVA智能仓储系统中储位分配问题研究  

Study on the storage assignment in KIVA robotic mobile fulfillment system

作　　者：姜伟 马骁 毛程远[1] 王天文 陈森封 高清平 JIANG Wei;MA Xiao;MAO Chengyuan;WANG Tianwen;CHEN Senfeng;GAO Qingping(Key Laboratory of Urban Rail Transit Intelligent Operation and Maintenance Technology&Equipment of Zhejiang Province,Zhejiang Normal University,Jinhua 321004,China;Railway Branch of Zhejiang Communications Construction Group CO.,LTD.,Hangzhou 310051,China;Smart Supply Chain Y Business Management Department of Jingdong Group,Beijing 100176,China)

机构地区：[1]浙江师范大学浙江省城市轨道交通智能运维技术与装备重点实验室,浙江金华321004 [2]浙江交工集团股份有限公司铁路分公司,浙江杭州310051 [3]京东集团智能供应链Y业务管理部,北京100176

出　　处：《浙江师范大学学报（自然科学版）》2021年第3期344-353,共10页Journal of Zhejiang Normal University:Natural Sciences

基　　金：浙江省自然科学基金资助项目(LY21G010005;LY18G030021);国家留学基金委资助项目(201808330034)。

摘　　要：亚马逊公司的KIVA智能仓储系统是目前正在使用且相对成熟的“货到人”拣选系统,在“货到人”拣选模式下如何分配货物的存储位置直接关系到KIVA智能仓储系统的拣选效率.依据ABC库存规则,实际中经常存在所需分配的货格数大于等于货架数的货品.基于该特点,对已有KIVA智能仓储系统中储位分配问题的数学模型进行改进,并提出了改进遗传算法.实验结果表明:改进模型的求解速度和求解规模都优于已有模型;改进遗传算法获得的近似解更接近于最优解.The KIVA mobile fulfilment system of Amazon,a"cargo-to-person"picking system that currently be used in practice was usually regarded as a relatively mature system.Under"cargo-to-person"picking mode,how to allocate the storage location of cargo was directly related to the picking efficiency of the KIVA mobile fulfilment system.According to ABC inventory rules,it was common in practice that the number of inventory bins for an item needed to be assigned was equal or greater than the total number of pods.Based on this characteristic,the commonly used mathematical model of the storage assignment problem in the KIVA mobile fulfilment system was improved,an improved genetic algorithm was proposed.The experimental results showed that the solution speed and solution scale of the improved model were superior to the existing ones.The approximate solution obtained by the improved genetic algorithm appeared more closer to the optimal solution.

关 键 词：货到人 储位分配 改进模型 改进遗传算法 

分 类 号：F253.4[经济管理—国民经济]