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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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    References listed on IDEAS

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    9. Choi, Tsan-Ming & Wen, Xin & Sun, Xuting & Chung, Sai-Ho, 2019. "The mean-variance approach for global supply chain risk analysis with air logistics in the blockchain technology era," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 178-191.
    10. Sadia Samar Ali & Rajbir Kaur & D. Jinil Persis & Raiswa Saha & Murugan Pattusamy & V. Raja Sreedharan, 2023. "Developing a hybrid evaluation approach for the low carbon performance on sustainable manufacturing environment," Annals of Operations Research, Springer, vol. 324(1), pages 249-281, May.
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    13. Satyendra Kumar Sharma & Praveen Ranjan Srivastava & Ajay Kumar & Anil Jindal & Shivam Gupta, 2023. "Supply chain vulnerability assessment for manufacturing industry," Annals of Operations Research, Springer, vol. 326(2), pages 653-683, July.
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