Arabian Journal for Science and Engineering

, Volume 44, Issue 8, pp 7351–7360 | Cite as

Resilient Supplier Selection Through Introducing a New Interval-Valued Intuitionistic Fuzzy Evaluation and Decision-Making Framework

  • Reza Davoudabadi
  • S. Meysam MousaviEmail author
  • Vahid Mohagheghi
  • Behnam Vahdani
Research Article - Systems Engineering


Adaptability to change is one of the essential requirements of the supply chain for organizations in a competitive environment. Development of resilience strategies is the key to achieving this goal. Another issue in supply chains is the necessity for a way of dealing with uncertainty. Therefore, fuzzy logic and numbers have been widely used to model the uncertainty in the problems. The purpose of this paper is to facilitate supply chain management by developing a new approach in resilient supplier selection problem. In this study, after gathering the judgment of decision makers (DMs) as linguistic variables and converting them to interval-valued intuitionistic fuzzy (IVIF) numbers, the weight of each criterion is determined based on an entropy index; then, the complex proportional assessment (COPRAS) method based on IVIF numbers is used for ranking the suppliers. Objective and subjective weights are calculated to determine weights of DMs. Finally, due to the advantages of the last aggregation approaches, weights of DMs and COPRAS scores are aggregated by the weighted aggregated sum product assessment method (WASPAS). Finally, the effectiveness of the proposed method is shown by using the method in two case studies from the literature.


Resilient supplier selection Supply chain management Objective and subjective weights Interval-valued intuitionistic fuzzy (IVIF) Last aggregation WASPAS 



The authors would like to thank anonymous referees for their valuable comments that have led to improvements.


  1. 1.
    Rajesh, R.; Ravi, V.: Supplier selection in resilient supply chains: a grey relational analysis approach. J. Clean. Prod. 86, 343–359 (2015)CrossRefGoogle Scholar
  2. 2.
    Gitinavard, H.; Foroozesh, N.; Mousavi, S.M.; Mohagheghi, V.: Soft computing based on a selection index method with risk preferences under uncertainty: applications to construction industry. Int. J. Comput. Syst. Eng. 4(4), 238–247 (2018)CrossRefGoogle Scholar
  3. 3.
    Vahdani, B.; Mousavi, S.M.; Tavakkoli-Moghaddam, R.; Hashemi, H.: A new enhanced support vector model based on general variable neighborhood search algorithm for supplier performance evaluation: a case study. Int. J. Comput. Intell. Syst. 10, 293–311 (2017)CrossRefGoogle Scholar
  4. 4.
    Foroozesh, N.; Gitinavard, H.; Mousavi, S.M.; Vahdani, B.: A hesitant fuzzy extension of VIKOR method for evaluation and selection problems under uncertainty. Int. J. Appl. Manag. Sci. 9(2), 95–113 (2017)CrossRefGoogle Scholar
  5. 5.
    Foroozesh, N.; Tavakkoli-Moghaddam, R.; Mousavi, S.M.: Sustainable-supplier selection for manufacturing services: a new failure mode and effects analysis model based on interval-valued fuzzy group decision-making. Int. J. Adv. Manuf. Technol. 95(9–12), 3609–3629 (2018)CrossRefGoogle Scholar
  6. 6.
    Ho, W.; Xu, X.; Dey, P.K.: Multi-criteria decision making approaches for supplier evaluation and selection: a literature review. Eur. J. Oper. Res. 202(1), 16–24 (2010)CrossRefzbMATHGoogle Scholar
  7. 7.
    Christopher, M.; Peck, H.: Building the resilient supply chain. Int. J. Logist. Manag. 15(2), 1–14 (2004)CrossRefGoogle Scholar
  8. 8.
    Azadeh, A.; Abdollahi, M.; Farahani, M. H.; Soufi, H.R.: Green-resilient supplier selection: an integrated approach. In: International IEEE Conference, Istanbul. July 26 (Vol. 28) (2014)Google Scholar
  9. 9.
    Tang, C.S.: Perspectives in supply chain risk management. Int. J. Prod. Econ. 103(2), 451–488 (2006)CrossRefGoogle Scholar
  10. 10.
    Hamel, G.; Valikangas, L.: The quest for resilience. Revista Icade. Revista de las Facultades de Derecho y Ciencias Económicas y Empresariales 62, 355–358 (2004)Google Scholar
  11. 11.
    Haldar, A.; Ray, A.; Banerjee, D.; Ghosh, S.: Resilient supplier selection under a fuzzy environment. Int. J. Manag. Sci. Eng. Manag. 9(2), 147–156 (2014)Google Scholar
  12. 12.
    Sahu, A.K.; Datta, S.; Mahapatra, S.S.: Evaluation and selection of resilient suppliers in fuzzy environment: exploration of fuzzy-VIKOR. Benchmark. Int. J. 23(3), 651–673 (2016)CrossRefGoogle Scholar
  13. 13.
    Haldar, A.; Ray, A.; Banerjee, D.; Ghosh, S.: A hybrid MCDM model for resilient supplier selection. Int. J. Manag. Sci. Eng. Manag. 7(4), 284–292 (2012)Google Scholar
  14. 14.
    Mohagheghi, V.; Mousavi, S.M.; Vahdani, B.: A new multi-objective optimization approach for sustainable project portfolio selection: a real world application under interval-valued fuzzy environment. Iranian J. Fuzzy Syst. 13(6), 41–68 (2016)MathSciNetGoogle Scholar
  15. 15.
    Mohagheghi, V.; Mousavi, S.M.; Aghamohagheghi, M.; Vahdani, B.: A new approach of multi-criteria analysis for the evaluation and selection of sustainable transport investment projects under uncertainty: a case study. Int. J. Comput. Intell. Syst. 10, 605–626 (2017)CrossRefGoogle Scholar
  16. 16.
    Atanassov, K.; Gargov, G.: Interval-valued intuitionistic fuzzy sets. Fuzzy Sets Syst. 31, 343–349 (1989)MathSciNetCrossRefzbMATHGoogle Scholar
  17. 17.
    Atanassov, K.T.: Intuitionistic fuzzy sets. Fuzzy Sets Syst. 20(1), 87–96 (1986)MathSciNetCrossRefzbMATHGoogle Scholar
  18. 18.
    Chen, T.Y.: IVIF-PROMETHEE outranking methods for multiple criteria decision analysis based on interval-valued intuitionistic fuzzy sets. Fuzzy Optim. Decis. Mak. 14(2), 173–198 (2015)MathSciNetCrossRefzbMATHGoogle Scholar
  19. 19.
    Li, D.F.: Extension principles for interval-valued intuitionistic fuzzy sets and algebraic operations. Fuzzy Optim. Decis. Mak. 10(1), 45–58 (2011)MathSciNetCrossRefzbMATHGoogle Scholar
  20. 20.
    Zhao, H.; Xu, Z.; Yao, Z.: Interval-valued intuitionistic fuzzy derivative and differential operations. Int. J. Comput. Intell. Syst. 9(1), 36–56 (2016)CrossRefGoogle Scholar
  21. 21.
    Garg, H.: A new generalized improved score function of interval-valued intuitionistic fuzzy sets and applications in expert systems. Appl. Soft Comput. 38, 988–999 (2016)CrossRefGoogle Scholar
  22. 22.
    Zhang, X.; Xu, Z.: Soft computing based on maximizing consensus and fuzzy TOPSIS approach to interval-valued intuitionistic fuzzy group decision making. Appl. Soft Comput. 26, 42–56 (2015)CrossRefGoogle Scholar
  23. 23.
    Dorfeshan, Y.; Mousavi, S.M.: A new interval type-2 fuzzy decision method with an extended relative preference relation and entropy to project critical path selection. Int. J. Fuzzy Syst. Appl. 8(1), 19–47 (2019)CrossRefGoogle Scholar
  24. 24.
    Chou, Y.C.; Yen, H.Y.; Sun, C.C.: An integrate method for performance of women in science and technology based on entropy measure for objective weighting. Qual. Quant. 48(1), 157–172 (2014)CrossRefGoogle Scholar
  25. 25.
    Jin, F.; Pei, L.; Chen, H.; Zhou, L.: Interval-valued intuitionistic fuzzy continuous weighted entropy and its application to multi-criteria fuzzy group decision making. Knowl. Based Syst. 59, 132–141 (2014)CrossRefGoogle Scholar
  26. 26.
    Yager, R.R.: OWA aggregation over a continuous interval argument with applications to decision making. IEEE Trans. Syst. Man Cybern. Part B (Cybern.) 34(4), 1952–1963 (2004)CrossRefGoogle Scholar
  27. 27.
    Shemshadi, A.; Shirazi, H.; Toreihi, M.; Tarokh, M.J.: A fuzzy VIKOR method for supplier selection based on entropy measure for objective weighting. Expert Syst. Appl. 38(10), 12160–12167 (2011)CrossRefGoogle Scholar
  28. 28.
    Liu, W.; Li, L.: An approach to determining the integrated weights of decision makers based on interval number group decision matrices. Knowl. Based Syst. 90, 92–98 (2015)CrossRefGoogle Scholar
  29. 29.
    Yue, Z.: A method for group decision-making based on determining weights of decision makers using TOPSIS. Appl. Math. Model. 35(4), 1926–1936 (2011)MathSciNetCrossRefzbMATHGoogle Scholar
  30. 30.
    Zavadskas, E.K.; Antucheviciene, J.; Hajiagha, S.H.R.; Hashemi, S.S.: Extension of weighted aggregated sum product assessment with interval-valued intuitionistic fuzzy numbers (WASPAS-IVIF). Appl. Soft Comput. 24, 1013–1021 (2014)CrossRefGoogle Scholar

Copyright information

© King Fahd University of Petroleum & Minerals 2019

Authors and Affiliations

  • Reza Davoudabadi
    • 1
  • S. Meysam Mousavi
    • 1
    Email author
  • Vahid Mohagheghi
    • 1
  • Behnam Vahdani
    • 2
  1. 1.Department of Industrial Engineering, Faculty of EngineeringShahed UniversityTehranIran
  2. 2.Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin BranchIslamic Azad UniversityQazvinIran

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