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Innovative supply chain optimization models with multiple uncertainty factors

Author

Listed:
  • Tsan-Ming Choi

    (The Hong Kong Polytechnic University)

  • Kannan Govindan

    (University of Southern Denmark)

  • Xiang Li

    (Nankai University)

  • Yongjian Li

    (Nankai University)

Abstract

Uncertainty is an inherent factor that affects all dimensions of supply chain activities. In today’s business environment, initiatives to deal with one specific type of uncertainty might not be effective since other types of uncertainty factors and disruptions may be present. These factors relate to supply chain competition and coordination. Thus, to achieve a more efficient and effective supply chain requires the deployment of innovative optimization models and novel methods. This preface provides a concise review of critical research issues regarding innovative supply chain optimization models with multiple uncertainty factors. It also introduces the special issue’s research papers and their respective insights.

Suggested Citation

  • Tsan-Ming Choi & Kannan Govindan & Xiang Li & Yongjian Li, 2017. "Innovative supply chain optimization models with multiple uncertainty factors," Annals of Operations Research, Springer, vol. 257(1), pages 1-14, October.
    • Handle: RePEc:spr:annopr:v:257:y:2017:i:1:d:10.1007_s10479-017-2582-4
    DOI: 10.1007/s10479-017-2582-4
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    10. B. C. Giri & J. K. Majhi & S. Bardhan & K. S. Chaudhuri, 2021. "Coordinating a three-level supply chain with effort and price dependent stochastic demand under random yield," Annals of Operations Research, Springer, vol. 307(1), pages 175-206, December.
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