ISyE Graduate Seminar: Integrating Anticipative Replenishment-Allocation with Reactive Fulfillment for Online Retailing Using Robust Optimization
Please join us for our next seminar of fall semester. This research seminar will feature Professor Yun Fong Lim of the Singapore Management University who will discuss integrating anticipative replenishment-allocation with reactive fulfillment for online retailing using robust optimization.
Livestreaming: Again this year we are coordinating with the Institute for Mathematics and its Applications to livestream our seminars on the IMA YouTube Channel. Attend in person or watch the livestream.
3:15 p.m. - Refreshments
3:30 p.m. - Graduate Seminar
Professor Yun Fong Lim
Lee Kong Chian School of Business
Singapore Management University
About the seminar
Aggressive expansion in e-commerce sales significantly escalates online retailers’ operating cost. In each period of a planning horizon, an online retailer decides on how much to replenish each product and how to allocate its inventory to fulfillment centers (FCs) before demand is known. After the demand in the period is realized, the retailer decides on which FCs to fulfill it. It is crucial to optimize the replenishment, allocation, and fulfillment decisions jointly such that the expected total operating cost is minimized. The problem is challenging because the replenishment-allocation is done in an anticipative manner under a “push” strategy, but the fulfillment is executed in a reactive manner under a “pull” strategy.
Lim and his colleagues propose a multi-period stochastic optimization model to delicately integrate the anticipative replenishment-allocation decisions with the reactive fulfillment decisions such that they are determined seamlessly as the demands are realized over time. His team develops a two-phase approach based on robust optimization to solve the problem. The first phase decides whether different products should be replenished in each period (binary decisions). Lim and his colleagues fix these binary decisions in the second phase, where they determine the replenishment, allocation, and fulfillment quantities.
Numerical experiments suggest that their approach outperforms existing methods from the literature in solution quality and computational time, and performs within 7 percent of a benchmark with perfect information. A study using data from a major fashion online retailer in Asia suggests that the two-phase approach can potentially reduce the retailer’s current cost by 30 percent. By decoupling the binary decisions from the continuous decisions, Lim's methodology can handle large problem instances (up to 1,200 products). The integration, robustness, and adaptability of the decisions under his approach create significant values.
About the speaker
Yun Fong Lim is an associate professor of operations management at the Lee Kong Chian School of Business at Singapore Management University (SMU). He is also a Chang Jiang Chair Professor, and has been a Lee Kong Chian Fellow and a Neptune Orient Lines Fellow. Lim’s research appears in Operations Research, Management Science, Manufacturing and Service Operations Management, and Production and Operations Management. He has delivered keynote and plenary speeches at several international conferences. In addition, his work has received funding by Singapore's Ministry of Education and Agency for Science, Technology and Research and media coverage by The Business Times, Channel 8, and CNA938. His current research interests include e-commerce and marketplace analytics, inventory management, warehousing and fulfillment, flexible workforce and resource management, and sustainable urban logistics.
Lim is a recipient of the SMU Teaching Excellence Innovative Teacher Award. He teaches both undergraduate and postgraduate courses in operations management. He has provided consulting service and executive development to corporations such as Maersk, McMaster-Carr Company, Resorts World Sentosa, Schneider Electrics, Temasek Holdings, and Zalora. Lim obtained both his Ph.D. and M.S. degrees in Industrial and Systems Engineering from the Georgia Institute of Technology.