并行自动拣选系统品项拣选量拆分优化  

SKU Picking Quantity Splitting Optimization of Parallel Automatic Picking System

作　　者：王艳艳[1] 吴耀华[1] 吴颖颖[1] 

机构地区：[1]山东大学控制科学与工程学院,济南250061

出　　处：《机械工程学报》2013年第16期177-184,共8页Journal of Mechanical Engineering

基　　金：国家自然科学基金资助项目(50175064)

摘　　要：分析并行自动分拣系统的作业模式,发现各分拣机的分拣延迟时间是影响分拣效率的关键因素之一,建立基于虚拟视窗的拣选时间模型;分析品项拣选量拆分对并行分拣系统分拣延迟时间模型的影响,建立大批量分拣时总分拣延迟时间最短为目标的拣选量拆分优化模型;提出并证明拣选量拆分优化的必要条件,降低模型求解的复杂度,并设计启发式自适应遗传算法对拣选量拆分优化模型进行求解,仿真结果显示与常用的拣选量平均拆分法相比拣选作业时间缩短9%左右。Through analyzing to the working pattern of parallel automated picking system,it is achieved that the delay time is one of the key factors which influence the picking efficiency and the picking time model is built based on virtual window.The shortest total delay time model of a large of orders is built through analyzing the relation of the delay time and the stock keeping unit（SKU） splitting picking quantity.To decrease computational complexity,the necessary conditions for SKU splitting picking quantity are proposed and proved.The heuristic adaptive genetic algorithm for SKU picking quantity splitting model is designed based on the necessary conditions.The simulation shows the algorithm can shorten the picking time about 9% than the average splitting method.

关 键 词：并行自动拣选系统 拣选量拆分 延迟时间 启发式自适应遗传算法 

分 类 号：F253[经济管理—国民经济]