IEOR - Designing a More Efficient World

Data-driven operations management paper selected as research competition finalist

IEOR assistant professor Zeyu Zheng, joint with Xiaocheng Li, Yufeng Zheng, and Zhenpeng Zhou, have been selected as finalists for the 2018 MSOM Data Driven Research Competition. Xiaocheng and Zeyu will present their paper “Demand Prediction, Predictive Shipping, and Product Allocation for Large-scale E-commerce” at the INFORMS Annual Meeting in Phoenix.

The paper can be found here.

Abstract: In this paper, we first extensively analyze the transactional level data made available by Alibaba and its logistics arm Cainiao, including detailed information on transaction orders, inventory and logistics for 7,103 different products and 130 warehouses. Based on the data analysis, we focus on demand prediction, data-driven shipping mechanisms, and product allocation across warehouses: (i) We develop a multiple-product demand prediction system that identifies unique features presented in the data, which improves prediction accuracy significantly compared to standard machine learning models. A new clustering-based regularization method is developed with the aid of representation learning to augment data and prevent overfitting. (ii) We propose and analyze in theory a novel shipping mechanism – Predictive Shipping, which utilizes demand prediction to arrange shipping before orders are placed. The observed vast vacancy in regional warehouses are utilized to support this mechanism. (iii) We formulate a large-scale product allocation problem across warehouses and study the cost sensitivity of a change in allocation distributions. Numerical experiments with both real data and synthetic data are conducted to illustrate our findings.

Vishrut Rana