基于改进贪婪关联算法的在线零售商优化拆单问题

doi:10.3969/j.issn.1007-7375.2021.02.017

工业工程 ›› 2021, Vol. 24 ›› Issue (2): 134-140.doi: 10.3969/j.issn.1007-7375.2021.02.017

基于改进贪婪关联算法的在线零售商优化拆单问题

钟丽文¹, 姜同强^1,2

1. 北京工商大学计算机与信息工程学院;
2. 农产品质量安全追溯技术及应用国家工程实验室，北京 100048

收稿日期:2019-11-21 发布日期:2021-04-25
通讯作者: 姜同强(1966-)，男，山东省人，教授，硕士，主要研究方向为智能信息管理。E-mail：jiangtq@btbu.edu.cn E-mail:jiangtq@btbu.edu.cn
作者简介:钟丽文(1995-)，女，福建省人，硕士研究生，主要研究方向为智慧物流
基金资助:
国家重点研发计划专项项目(2019YFC1606400)；国家重点研发计划(2016YFD0401205)

Online Retailer Optimal Splitting Problem Based on Improved Greedy Association Algorithm

ZHONG Liwen¹, JIANG Tongqiang^1,2

1. School of Computer and Information Engineering;
2. National Engineering Laboratory for Agri-product Quality Traceability, Beijing Technology and Business University, Beijing 100048, China

Received:2019-11-21 Published:2021-04-25

摘要/Abstract

摘要： 针对在线零售商一地多仓及仅考虑品类拆单的场景，建立最大化整单配送模型，对单品分配方法进行研究，目的是通过改进现有算法优化配送中心中存放的单品，以进一步降低拆单率。针对贪婪订单算法和贪婪热销算法中未考虑单品间关系性的问题，结合Apriori算法，对算法进行优化设计，提出贪婪关联算法。算法应用一种新的单品分配方法寻求订单中具有强关联关系的单品，并对具有强关联关系的单品优先进行分配。实验结果表明，与贪婪订单算法和贪婪热销算法相比，改进后的算法能显著地降低拆单率，分别降低约8%和11%。

关键词: 在线零售, 一地多仓, 单品分配, 拆单率

Abstract: For the scene where the online retailer has multiple warehouses in one region and only considers the case of split due to stock item, is a model established for maximizing the entire order distribution, and the stock item allocation method is studied, to improve the existing algorithms to optimize the items stored in the distribution center to further reduce the order split rate. Aiming at the problem of the Greedy Order Algorithm and the Greedy Hot Sale Algorithm not considering the relationship between items, and combining with Apriori Algorithm, the algorithm is optimized and designed, and a Greedy Association Algorithm is proposed. The algorithm uses a new method of item allocation to find the stock items with strong correlation, and priority is given to the stock items with strong correlation.The experimental results show that compared with the Greedy Order Algorithm and the Greedy Sales Algorithm, the improved algorithm can significantly reduce the rate of order splitting by approximately 8% and 11%, respectively.

Key words: online retail, multiple warehouses in one region, stock item allocation, order split rate

中图分类号:

F274

钟丽文, 姜同强. 基于改进贪婪关联算法的在线零售商优化拆单问题[J]. 工业工程, 2021, 24(2): 134-140.

ZHONG Liwen, JIANG Tongqiang. Online Retailer Optimal Splitting Problem Based on Improved Greedy Association Algorithm[J]. Industrial Engineering Journal, 2021, 24(2): 134-140.

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基于改进贪婪关联算法的在线零售商优化拆单问题

Online Retailer Optimal Splitting Problem Based on Improved Greedy Association Algorithm

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