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Real-time procurement policy with yield and price uncertainty

Author

Listed:
  • Wenqiang Dai
  • Zhuolin Yang
  • Yi Feng
  • Meng Zheng

Abstract

This study formulates and analyses a procurement model in which a procurer faces both yield and price uncertainty. We propose a simple and effective real-time procurement policy where the decisions are made only based on the current arriving price and inventory level. The only information we need is the first two moments for the random yield rate, and the lower and upper bounds for price. Thus, our policy delivers robust performance to changing yield and price over time. In addition, simple decision rules are summarised for determining the optimal procurement quantity for different cases. Analytical results and numerical experiments are presented to show that the proposed policy achieves a superior performance guarantee.

Suggested Citation

  • Wenqiang Dai & Zhuolin Yang & Yi Feng & Meng Zheng, 2020. "Real-time procurement policy with yield and price uncertainty," International Journal of Production Research, Taylor & Francis Journals, vol. 58(3), pages 758-782, February.
  • Handle: RePEc:taf:tprsxx:v:58:y:2020:i:3:p:758-782
    DOI: 10.1080/00207543.2019.1600761
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    Cited by:

    1. Wenqiang Dai & Meng Zheng & Xu Chen & Zhuolin Yang, 0. "Online economic ordering problem for deteriorating items with limited price information," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-23.
    2. Maheshwari, Pratik & Kamble, Sachin & Belhadi, Amine & Venkatesh, Mani & Abedin, Mohammad Zoynul, 2023. "Digital twin-driven real-time planning, monitoring, and controlling in food supply chains," Technological Forecasting and Social Change, Elsevier, vol. 195(C).
    3. Wenqiang Dai & Meng Zheng & Xu Chen & Zhuolin Yang, 2022. "Online economic ordering problem for deteriorating items with limited price information," Journal of Combinatorial Optimization, Springer, vol. 44(4), pages 2246-2268, November.

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