Dynamic lot-sizing models for retailers with online channels

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• 作者：Haoxuan Xu^a ; ^{haoxuanxu@znufe.edu.cn} ; Yeming (Yale) Gong^b ; ^{GONG@em-lyon.com} ; Chengbin Chu^c ; ^{chengbin.chu@centralesupelec.fr} ; Jinlong Zhang^d ; ^{jlzhang@hust.edu.cn}
• 关键词：Dynamic programming ; Online retailing ; Dynamic lot-sizing ; Advance demand information
• 刊名：International Journal of Production Economics
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：183
• 期：part_PA
• 页码：171-184
• 全文大小：1311 K
• 卷排序：183

文摘

This paper studies inventory replenishment planning problems for retailers with online channels. Such retailer is able to obtain advance demand information (ADI) in an environment of time-varying demands. We incorporate ADI into dynamic lot-sizing models to formulate the replenishment planning problems for retailers in three scenarios: (1) companies act as pure-play online retailers with customers homogeneous in demand lead time, (2) online customers are heterogeneous in demand lead time with priorities, and (3) retailers operate in a bricks-and-clicks structure, in which demands come from online and offline channels, with either independent or interactive channels. We formulate the problem in the general scenario of interactive demand channels as a mixed-integer linear programming model, and then develop a unified model through reformulation. Based on the optimality properties, we design a dynamic programming algorithm with polynomial running time to solve the unified model. The numerical experiments for several online retailers find that the method can significantly reduce the total inventory cost.