This project studies data-driven operations in E-commerce and other applications, with the target of proving business analytical decisions and optimization through mathematical modelling, and further uncovering managerial insights.
The importance lies in the fact that business practice needs theory-based polices, and the challenge is that how to model the real situation properly and how to make the model more robust to all kinds of uncertainties.
Online decision, asymptotic analysis, simulation based method
Provide rigorous performance bound analysis for proposed policy and algorithms, with important implication that simple algorithm can lead to good results.
Building models, theoretical analysis, data collection and mode calibration, numerical experiments.
Opaque selling: Preliminary results
Xu, Z., H. Zhang, J. Zhang and R. Zhang (2020). Online Demand Fulllment under Limited Flexibility." Management Science.
Long Z., N. Shimkin, H. Zhang and J. Zhang (2020). Dynamic Scheduling for Multiclass Many-server Queues with Abandonment: the Generalized c =h Rule."Operations Research.
Zhang, H., J. Zhang and R. Zhang (2020). Simple Policies with Provable Bounds for Managing Perishable Inventory". Production and Operations Management.
Wang G., H. Zhang and J. Zhang. On-demand Matching in a Spacial Model with Abandonment.", Major revision with Operations Research.
Zhang, H., J. Zhang and R. Zhang. Optimal control of production systems with limited flexibility under continuous review."
Fan, X., H.Zhang. The Role of Government Funding in Firm's Investment Decision: Promoting Innovation or Accelerating Bankruptcy?"
Lixiang Lia, M. Lia, H. Zhang, L. Zhang. Pricing Optimization under the Extended
Nested Logit Model"， submitted.