文章基本信息

标题：POSデータに基づく欠品時の顧客行動を考慮した小売店舗の購買シミュレーション
本地全文：下载
作者：松村直樹 ; 和泉潔 ; 山田健太等
期刊名称：人工知能学会論文誌
印刷版ISSN：1346-0714
电子版ISSN：1346-8030
出版年度：2016
卷号：31
期号：2
页码：F-F13_1-8
DOI：10.1527/tjsai.F-F13
出版社：The Japanese Society for Artificial Intelligence
摘要：Controlling the trade-off between the costs of disposal and losses of stock shortage have been one of the big management issue in retail stores, especially in convenient stores dealing many products of short expiration date. In this study, we aimed to evaluate the maximum gross profit and to analyze transition of waste costs and losses of purchasing opportunities in a retail store. We have developed a model of a retail store which performs simple three types of demand estimation and three types of ordering, and also created a model of customers which reflects consumer reactions to out-of-shelf situations such as brand switches and cancel purchasing by using actual Point-of-Sales and stock data. As a result of experiments by agent-based simulation, we obtained the order quantity to maximize the gross profit when the retail store made quantitative ordering. Moreover, we found that providing thresholds in minimum order amount increased gross profit and reduced losses of shortage. Finally, the combination of the demand estimation by using exponential smoothing and the threshold ordering made better performance than any other method.
关键词：multi-agent simulation;out-of-shelf;brand switch;convenience store