Shipping Consolidation Across Two Warehouses with Delivery Deadline and Expedited Options for E-commerce and Omni-channel Retailers

合并(业务) 启发式 计算机科学 运筹学 灵活性(工程) 经济短缺 业务 经济 工程类 财务 语言学 操作系统 哲学 管理 政府(语言学)
作者
Lai Wei,Roman Kapuściński,Stefanus Jasin
出处
期刊:Manufacturing & Service Operations Management [Institute for Operations Research and the Management Sciences]
卷期号:23 (6): 1634-1650 被引量:37
标识
DOI:10.1287/msom.2020.0903
摘要

Problem definition: Shipment consolidation (i.e., shipping multiple orders together instead of shipping them separately) is commonly used to decrease total shipping costs. However, when the delivery of some orders is delayed, so they can be consolidated with future orders, a more expensive expedited shipment may be needed to meet shorter deadlines. In this paper, we study the optimal consolidation policy focusing on the trade-off between economies of scale due to combining orders and expedited shipping costs, in the setting of two warehouses. Academic/practical relevance: Our work is motivated by the application of fulfillment consolidation in e-commerce and omni-channel retail, especially with the rise of so-called on-demand logistics services. Sellers have the flexibility to take advantage of consolidation by deciding when to ship the orders and from which warehouse to fulfill the orders, as long as the orders’ deadlines are met. Methodology: We use Dynamic Programming to study the optimal policy and its structure. We also conduct extensive simulation tests to evaluate the performance of heuristics that are based on structures of the optimal policies. Results: The optimal policies and their structures are characterized. Using the insights of these structural properties, we propose two easily implementable heuristics that perform within 1%–2% of the optimal solution and outperform other benchmark consolidation methods in numerical tests. Managerial implications: Consolidation is shown to significantly reduce the outbound shipping costs. Retailers can take advantage of it to effectively improve the standard policies by simply applying the threshold-form heuristics we propose.
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