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Optimization of Strategic Alliance Supply Chain Logistics Planning Under Uncertain Environment

In: Optimization of Integrated Supply Chain Planning under Multiple Uncertainty

Author

Listed:
  • Juping Shao

    (Suzhou University of Science and Technology)

  • Yanan Sun

    (Suzhou Industrial Park Anwood Logistics System Co., Ltd)

  • Bernd Noche

    (University Duisburg-Essen)

Abstract

Very often the market demand and the price of the finished products that the supply chain provides are uncertain. Even for a strategic alliance supply chain which has a dominant core business, what it can coordinate and control is only limited to the supply and demand, price and other related information between node enterprises inside the supply chain. In the face of rapidly changing external market, it is difficult to determine parameters like the quantity of demand and price exactly. But decision makers can derive a probability distribution function of the changing within the market demand and the price of the product through the analysis of the historical data of demand and price. In other words, we can use random variables to describe such uncertain parameters as demand quantity and price.

Suggested Citation

  • Juping Shao & Yanan Sun & Bernd Noche, 2015. "Optimization of Strategic Alliance Supply Chain Logistics Planning Under Uncertain Environment," Springer Books, in: Optimization of Integrated Supply Chain Planning under Multiple Uncertainty, edition 127, chapter 0, pages 57-99, Springer.
    • Handle: RePEc:spr:sprchp:978-3-662-47250-7_4
    DOI: 10.1007/978-3-662-47250-7_4
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    Cited by:

    1. Khishtandar, Soheila, 2019. "Simulation based evolutionary algorithms for fuzzy chance-constrained biogas supply chain design," Applied Energy, Elsevier, vol. 236(C), pages 183-195.

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