基于FP-Tree 算法的仓库货位优化研究  

RESEARCH ON WAREHOUSE LOCATION OPTIMIZATION BASED ON FP-TREE ALGORITHM

作　　者：陈荣[1] 付林萍 王锐 张水旺 CHEN Rong;FU Lin-ping;WANG Rui;ZHANG Shui-wang(School of Management Science and Engineering,Anhui University of Technology,Maanshan 243032,China)

机构地区：[1]安徽工业大学管理科学与工程学院,安徽马鞍山243032

出　　处：《南阳理工学院学报》2020年第6期6-11,共6页Journal of Nanyang Institute of Technology

基　　金：2016年安徽工业大学青年校级课题(RD16100269);2017年安徽省社会科学创新发展研究课题(2017CX030);2018年安徽省高校人文社科重点项目(SK2018A0064)。

摘　　要：货位优化是降低系统成本提高客户满意度的有效途径之一。本文首先运用FP-Tree算法获取频繁项集,并构建了以提高货架稳定性、减少订单拣选距离为目标的货位优化模型,再利用理想点法,建立了按照权重综合的多目标优化评价函数,最后利用遗传算法进行仿真求解。结果表明FP-Tree算法通过挖掘相关货物关联规则减少订单拣选距离从而实现货位优化,是降低仓库管理成本、提高仓库管理效率与效益的有效方法与途径。Location optimization is one of the effective ways to reduce system cost and improve customer satisfaction.First,this paper uses the FP-Tree algorithm to obtain frequent itemset.Then,based on the ideal point method,the multi-objective of shelf stability and order picking distance is transformed into a single objective.Last,the genetic algorithm is used to solve the problem.The result shows that using obtaining frequent itemset,FP-Tree algorithm can significantly reduce walking distance of orders,which is an effective way to reduce the cost of warehouse management and improve the efficiency and benefit of warehouse management.

关 键 词：FP-TREE算法 货位优化 遗传算法 

分 类 号：F252[经济管理—国民经济] O22[理学—运筹学与控制论]