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Sourcing decision under disruption risk with supply and demand uncertainty: A newsvendor approach

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  • Pritee Ray
  • Mamata Jenamani

Abstract

Multi-sourcing is considered as a common practice to hedge against supply disruption risk. In this context, this paper proposes two models for optimal order allocation in newsvendor setting, where both supply and demand are uncertain. The first model considers a risk neutral decision maker who maximizes the total expected profit under disruption risk. The second one is for a risk averse decision maker who does so under service level constraints. Analytical closed form solutions for both the models are derived. To overcome the computational complexity of the exact optimal solution, two algorithms are developed to generate optimal order quantity and the corresponding set of suppliers. The solutions with exact optimization algorithms and the proposed ones are illustrated and compared with numerical examples. The results show that the proposed algorithms give the exact optimal solution while being tractable. Finally, a case study is used to illustrate the applicability of the proposed model. Copyright Springer Science+Business Media New York 2016

Suggested Citation

  • Pritee Ray & Mamata Jenamani, 2016. "Sourcing decision under disruption risk with supply and demand uncertainty: A newsvendor approach," Annals of Operations Research, Springer, vol. 237(1), pages 237-262, February.
  • Handle: RePEc:spr:annopr:v:237:y:2016:i:1:p:237-262:10.1007/s10479-014-1649-8
    DOI: 10.1007/s10479-014-1649-8
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    4. Md. Tarek Chowdhury & Aditi Sarkar & Sanjoy Kumar Paul & Md. Abdul Moktadir, 2022. "A case study on strategies to deal with the impacts of COVID-19 pandemic in the food and beverage industry," Operations Management Research, Springer, vol. 15(1), pages 166-178, June.
    5. Xu, Jianjun & Keblis, Matthew F. & Feng, Youyi & Chang, Yanling, 2017. "Optimal sourcing from a pool of suppliers with nonidentical salvage values," International Journal of Production Economics, Elsevier, vol. 193(C), pages 392-405.
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    8. Mori, Masakatsu & Kobayashi, Ryoji & Samejima, Masaki & Komoda, Norihisa, 2017. "Risk-cost optimization for procurement planning in multi-tier supply chain by Pareto Local Search with relaxed acceptance criterion," European Journal of Operational Research, Elsevier, vol. 261(1), pages 88-96.
    9. Garvey, Myles D. & Carnovale, Steven, 2020. "The rippled newsvendor: A new inventory framework for modeling supply chain risk severity in the presence of risk propagation," International Journal of Production Economics, Elsevier, vol. 228(C).
    10. Federico Toffano & Michele Garraffa & Yiqing Lin & Steven Prestwich & Helmut Simonis & Nic Wilson, 2022. "A multi-objective supplier selection framework based on user-preferences," Annals of Operations Research, Springer, vol. 308(1), pages 609-640, January.
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    14. PrasannaVenkatesan, S. & Goh, M., 2016. "Multi-objective supplier selection and order allocation under disruption risk," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 124-142.
    15. Kelei Xue & Yongjian Li & Xueping Zhen & Wen Wang, 2020. "Managing the supply disruption risk: option contract or order commitment contract?," Annals of Operations Research, Springer, vol. 291(1), pages 985-1026, August.
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    17. Sanjoy Kumar Paul & Priyabrata Chowdhury, 2020. "Strategies for Managing the Impacts of Disruptions During COVID-19: an Example of Toilet Paper," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 21(3), pages 283-293, September.

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