6 papers
Resource-Adaptive Primal-Dual Learning for One-Warehouse Multi-Store Systems with Censored Demand
Jiameng Lyu
The one-warehouse multi-store (OWMS) system is a fundamental inventory network in which a nonreplenishable warehouse allocates shared stock across multiple stores over time. Existi…
Allocating Human Oversight in AI-Enabled Analytics
Zikun Ye, Jiameng Lyu, Rui Tao
Organizations increasingly deploy AI as a low-cost prediction layer in customer-facing decision processes, including demand sensing, service-quality monitoring, product testing, an…
Learning in Position-Aware Multinomial Logit Bandits: From Multiplicative to General Position Effects
Xi Chen, Shibo Dai, Jiameng Lyu +1
We study the dynamic joint assortment selection and positioning problem, where the attraction of each product depends on both its intrinsic appeal and its display position under a…
Learning When to Restart: Nonstationary Newsvendor from Uncensored to Censored Demand
Xin Chen, Jiameng Lyu, Shilin Yuan +1
We study nonstationary newsvendor problems under nonparametric demand models and general distributional measures of nonstationarity, addressing the practical challenges of unknown…
A Minibatch-SGD-Based Learning Meta-Policy for Inventory Systems with Myopic Optimal Policy
Jiameng Lyu, Jinxing Xie, Shilin Yuan +1
Stochastic gradient descent (SGD) has proven effective in solving many inventory control problems with demand learning. However, it often faces the pitfall of an infeasible target…
Regret Optimality of Sample Average Approximation for Data-Driven Newsvendor Problems: A General Optimization Perspective
Jiameng Lyu, Shilin Yuan, Bingkun Zhou +1
Numerous existing studies have examined the performance of Sample Average Approximation (SAA) in the fundamental newsvendor problem. Despite these advances, critical gaps remain in…