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Data-Driven Joint Pricing and Inventory Management Newsvendor Problem

In: AI and Analytics for Smart Cities and Service Systems

Author

Listed:
  • Pengxiang Zhou

    (Tsinghua University)

  • Wai Kin (Victor) Chan

    (Tsinghua University)

Abstract

Data-driven methods are proposed to optimize both pricing and inventory management strategies in price and quantity setting newsvendor problem. Simulation experiments show that prescriptive method and casual sample average approximation outperform Predict-then-Optimize method. Sample average approximation might be even worse when ignoring pricing effect on demand uncertainty.

Suggested Citation

  • Pengxiang Zhou & Wai Kin (Victor) Chan, 2021. "Data-Driven Joint Pricing and Inventory Management Newsvendor Problem," Lecture Notes in Operations Research, in: Robin Qiu & Kelly Lyons & Weiwei Chen (ed.), AI and Analytics for Smart Cities and Service Systems, pages 397-403, Springer.
    • Handle: RePEc:spr:lnopch:978-3-030-90275-9_31
    DOI: 10.1007/978-3-030-90275-9_31
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