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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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The boom of e-commerce in the globe in recent years has expedited the expansion of fulfillment infrastructures by e-retailers. While e-retailers are building more warehouses to offer faster delivery service than ever, the associated fulfillment costs have skyrocketed over the past decade. In this paper, we study the problem of minimizing fulfillment costs, in which an e-retailer must decide which warehouse(s) to fulfill each order from, subject to warehouses’ inventory constraints. The e-retailer can split an order, at an additional cost, and fulfill it from different warehouses. It is notoriously challenging to make effective real-time fulfillment decisions at the occurrence of order split, which has become a major problem for e-retailers.
We focus on a two-layer distribution network that has been implemented in practice by major e-retailers. We analyze the performance of fulfillment policies that do not rely on demand forecasts. We show that, under an assumption that aligns with the practice of most e-retailers, a myopic policy achieves a constant performance ratio compared to an optimal clairvoyant algorithm. We further show that this ratio is tight. More generally, we characterize the performance guarantees of the myopic policy in terms of the cost param- eters of the model. Finally, we complement our theoretical results by conducting a numerical study and demonstrate the good performance of the myopic policy.
This is joint work with Xinshang Wang (Alibaba) and Yanyang Zhao (Chicago Booth).
Bio:
Linwei Xin is an assistant professor of Operations Management at the University of Chicago Booth School of Business. He graduated from ISyE in 2015, advised by David A. Goldberg and Alexander Shapiro. His research interests include supply chain, inventory and revenue management, optimization under uncertainty, and data-driven decision-making. His work has been recognized with several INFORMS paper competition awards, including the 2019 Applied Probability Society Best Publication Award, First Place in the 2015 George E. Nicholson Student Paper Competition, Second Place in the 2015 Junior Faculty Interest Group Paper Competition, and a finalist in the 2014 Manufacturing and Service Operations Management Student Paper Competition. His research has been published in journals such as Operations Research and Management Science. He won a NSF grant as PI. He also has worked with companies/organizations through research collaboration including Alibaba Group and Walmart Global eCommerce.
