网络零售供需匹配的最优政策和启发式方法

Qiyuan Deng, Xiaobo Li, Yun Fong Lim, Fang Liu
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摘要

问题定义:我们考虑一个在线零售商在有限的时间跨度内向不同地区销售多种产品。在时间跨度开始时,零售商从单一供应商处订购产品,并将其存储在多个仓库中。零售商根据其产能约束确定产品的订单量和每个仓库的存储量。在每个周期结束时,当该周期的随机需求实现后,零售商从每个仓库中选择检索数量,以满足每个区域的需求。目标是在有限的时间跨度内使零售商的预期利润最大化。方法/结果:对于单区情况,我们证明多期问题等同于单期问题,最优检索决策遵循贪婪策略,即从成本最低的仓库检索产品。我们设计了一种非贪婪算法来找到最优存储策略,它保留了嵌套属性:在所有非空仓库中,小索引仓库包含了大索引仓库中存储的所有产品。我们还分析了最优排序策略的特征。不幸的是,多区情况在分析上是难以解决的,因此我们提出了一种高效的启发式方法来解决这一问题,其中涉及三种近似方法的非难混合。在我们的数值实验中,这种混合启发式的性能分别比两个传统基准高出 22.5% 和 3.5%,实验条件包括各种期限长度、履行频率、仓库容量、需求变化和需求相关性。管理意义:基于亚洲一家大型时尚在线零售商数据的案例研究证实了混合启发式的优越性。通过精细优化,启发式方法比零售商采用的专用策略提高了 16% 的平均利润。对于具有各种结构的大型网络,混合启发式的表现继续优于基准:X. Li 由新加坡教育部 [Tier 1 Grant 23-0619-P0001] 资助。Y. F. Lim 感谢新加坡管理大学海事与港务局研究奖学金和新加坡教育部 [Tier 1 Grant MSS23B001] 的支持:在线附录见 https://doi.org/10.1287/msom.2021.0394 。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal Policies and Heuristics to Match Supply with Demand for Online Retailing
Problem definition: We consider an online retailer selling multiple products to different zones over a finite horizon with multiple periods. At the start of the horizon, the retailer orders the products from a single supplier and stores them at multiple warehouses. The retailer determines the products’ order quantities and their storage quantities at each warehouse subject to its capacity constraint. At the end of each period, after random demands in the period are realized, the retailer chooses the retrieval quantities from each warehouse to fulfill the demands of each zone. The objective is to maximize the retailer’s expected profit over the finite horizon. Methodology/results: For the single-zone case, we show that the multiperiod problem is equivalent to a single-period problem and the optimal retrieval decisions follow a greedy policy that retrieves products from the lowest-cost warehouse. We design a nongreedy algorithm to find the optimal storage policy, which preserves a nested property: Among all nonempty warehouses, a smaller-index warehouse contains all the products stored in a larger-index warehouse. We also analytically characterize the optimal ordering policy. The multizone case is unfortunately intractable analytically, and we propose an efficient heuristic to solve it, which involves a nontrivial hybrid of three approximations. This hybrid heuristic outperforms two conventional benchmarks by up to 22.5% and 3.5% in our numerical experiments with various horizon lengths, fulfillment frequencies, warehouse capacities, demand variations, and demand correlations. Managerial implications: A case study based on data from a major fashion online retailer in Asia confirms the superiority of the hybrid heuristic. With delicate optimization, the heuristic improves the average profit by up to 16% compared with a dedicated policy adopted by the retailer. The hybrid heuristic continues to outperform the benchmarks for larger networks with various structures.Funding: X. Li is supported by the Singapore Ministry of Education [Tier 1 Grant 23-0619-P0001]. Y. F. Lim is grateful for the support from the Singapore Management University under the Maritime and Port Authority Research Fellowship and the Singapore Ministry of Education [Tier 1 Grant MSS23B001].Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2021.0394 .
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