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Resilient Supplier Selection Based on Fuzzy BWM and GMo-RTOPSIS under Supply Chain Environment

Author

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  • Jiawu Gan
  • Shuqi Zhong
  • Sen Liu
  • Dan Yang

Abstract

Resilient suppliers can reduce supply chain risk, effectively avoid supply chain disruption, and bring profits to enterprises. However, there is no united measuring index system to evaluate the resilient supplier under supply chain environment, and the assessment language sets are usually crisp values. Therefore, in order to fill the research gap, this paper proposes a hybrid method, which combines triangular fuzzy number, the best-worst method (BWM), and the modular TOPSIS in random environments for group decision-making (GMo-RTOPSIS) to solve the above problem. Firstly, the weight of decision-maker is calculated by using fuzzy BWM which can deal with triangular fuzzy numbers. Secondly, triangular fuzzy number is introduced into GMo-RTOPSIS, and combined with fuzzy BWM, alternatives are sorted to select the best resilient supply chain partner. Finally, the feasibility and universality of this method are proved by illustrative examples.

Suggested Citation

  • Jiawu Gan & Shuqi Zhong & Sen Liu & Dan Yang, 2019. "Resilient Supplier Selection Based on Fuzzy BWM and GMo-RTOPSIS under Supply Chain Environment," Discrete Dynamics in Nature and Society, Hindawi, vol. 2019, pages 1-14, April.
    • Handle: RePEc:hin:jnddns:2456260
    DOI: 10.1155/2019/2456260
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    Cited by:

    1. Madjid Tavana & Salman Nazari-Shirkouhi & Hamidreza Farzaneh Kholghabad, 2021. "An integrated quality and resilience engineering framework in healthcare with Z-number data envelopment analysis," Health Care Management Science, Springer, vol. 24(4), pages 768-785, December.
    2. Yazdani, Morteza & Torkayesh, Ali Ebadi & Chatterjee, Prasenjit & Fallahpour, Alireza & Montero-Simo, Maria Jose & Araque-Padilla, Rafael A. & Wong, Kuan Yew, 2022. "A fuzzy group decision-making model to measure resiliency in a food supply chain: A case study in Spain," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    3. Sourour Aouadni & Jalel Euchi, 2022. "Using Integrated MMD-TOPSIS to Solve the Supplier Selection and Fair Order Allocation Problem: A Tunisian Case Study," Logistics, MDPI, vol. 6(1), pages 1-18, January.
    4. Alptekin Ulutaş & Mladen Krstić & Ayşe Topal & Leonardo Agnusdei & Snežana Tadić & Pier Paolo Miglietta, 2024. "A Novel Hybrid Gray MCDM Model for Resilient Supplier Selection Problem," Mathematics, MDPI, vol. 12(10), pages 1-22, May.
    5. Anas A. Makki & Reda M. S. Abdulaal, 2023. "A Hybrid MCDM Approach Based on Fuzzy MEREC-G and Fuzzy RATMI," Mathematics, MDPI, vol. 11(17), pages 1-19, September.

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