In the broadest sense, I do research regarding how to bridge operations research, statistics and machine learning together. I have a particular interest in studying multi-stage stochastic systems where data-driven decision making is involved, and their applications in supply chain analytics, revenue management and transportation systems.
- K. Ledvina, H. Qin, D. Simchi-Levi, Y. Wei. "A New Approach for Vehicle Routing with Stochastic Demand: Combining Route Assignment with Process Flexibility", Operations Research (2022). [link][SSRN]
- Supply Chain Management SIG Meeting, MSOM Conference 2021
- H. Qin, D. Simchi-Levi, L. Wang. "Data-Driven Approximation Schemes for Joint Pricing and Inventory Control Models", Management Science (2022). [link] [SSRN]
- H. Qin, D. Simchi-Levi, R. Ferer, J. Mays, K. Merriam, M. Forrester, A. Hamrick. "Trading Safety Stock for Service Response Time in Inventory Positioning", Production and Operations Management (2022). [link][SSRN].
- The 30th Anniversary Issue of Production and Operations Management
- H. Qin, Z. Zhang, D. Bai. "Permutation Flowshop Group Scheduling with Position-Based Learning Effect." Computers & Industrial Engineering 92 (2016): 1-15. [link]
- H. Hu, H. Qin, D. Simchi-Levi. "Solving Large-Scale Vehicle Routing Problems with Unsplit Demands via Limited Information", working paper. [SSRN]
- H. Qin, D. Simchi-Levi, R. Zhu. "Provably Sample-Efficient Inventory Control", submitted. [tech report]
- L. Chen, R. Jin, H. Qin, D. Simchi-Levi, Z. Zhang. "Distributionally Robust Omnichannel Stocking Decisions in Quick Fulfillment Systems", working paper. [SSRN]