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Manuscript ID : JEST-1702-3398 (R1) Visit : 117 Page: 201 - 212

10.30495/jest.2019.24940.3398

Article Type: Original Research

Resilient Suppliers Evaluation Using Fuzzy Ratio System and ANP Method

Subject Areas : Sustainable Development

Hashem Moazzez 1 , Mohammad Reza Fathi 2 , Davood Ramezani Kermani 3

1 - Assistant Professor., Department of Management and Accounting, College of Farabi, University of Tehran, Qom, Iran
2 - Assistant Professor., Department of Management and Accounting, College of Farabi, University of Tehran, Qom, Iran*(Correspondence Author)
3 - M.S of Industrial Management, Department of Management and Accounting, College of Farabi, University of Tehran, Qom, Iran

Received: 2017-02-18 Accepted : 2017-08-16 Published : 2021-03-21

Keywords: MADM, ANP, Resilient, Supplier, Fuzzy Ratio System,

Abstract :

Background and Objective: Proper management of a supply chain, assessment and selection of suppliers is an important task which can affect the profitability of organization in the long time. The purpose of this research is to provide a framework for assessing Resilient Suppliers.Material and Methods: Researcher through literature review and interviews with experts of Company and preparing a questionnaire to identify the factors affect to Resilient Suppliers. In this study, two ANP techniques to determine the weighting of criteria and Fuzzy Ratio System method for ranking alternatives are used.Results: The criteria and factors that influence the selection of resilient suppliers include the main factors of performance, minimization of risk, responsiveness, Technical support and power. In this study paired comparisons carried out by ANP. In addition, Fuzzy Ratio System as a new method of fuzzy multi-criteria decision-making, in order to rank the options is used.Conclusion: According to the results of Fuzzy Ratio System, S2 has been chosen as the best option.

References:



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_||_


  1. Gong, J., Mitchell, J. E., Krishnamurthy, A., & Wallace, W. A. (2014). An interdependent layered network model for a resilient supply chain. Omega, 46, 104-116.
    2.
  2. Haldar, A., Ray, A., Banerjee, D., & Ghosh, S. (2014). Resilient supplier selection under a fuzzy environment, International Journal of Management Science and Engineering Management, 9(2), 147-156.
    3.
  3. Hamel, G. and Valikangas, L. (2003). The quest for resilience, Harvard Business Review, 81(9), 52–63.
    4.
  4. Mitroff, I.I. and Alpasan, M. . (2003). Preparing for the evil, Harvard Business Review, 81(4), 109–115.
    5.
  5. Manuj, I. and Mentzer, J. (2008). Global supply chain risk management strategies. International Journal of Physical Distribution & Logistics Management, 38(3), 192–223.
    6.
  6. Sheffi, Y. (2005). Building a resilient supply chain, Harvard Business Review Supply Chain Strategy 1(5), 1-11.
    7.
  7. Briano, E., Caballini, C., & Revetria, R. (2009). Literature review about supply chain vulnerability and resiliency. In Proceedings of the 8th WSEAS international conference on System science and simulation in engineering, 191-197.
    8.
  8. Banaeian, N., Mobli, H., Fahimnia, B., Nielsen, I. E., & Omid, M. (2016). Green Supplier Selection Using Fuzzy Group Decision Making Methods: A Case Study from the Agri-Food Industry, Computers & Operations Research, 89, 337-347.
    9.
  9. Rajabani, N., & Fathi, M. R. (2014). Proposing the Framework for Selecting the Best Sustainable Supplier Using Fuzzy Prioritization Method, Global Journal of Management Studies and Researches, 1(2), 100-108.
    10.
  10. Mohaghar, A., Fathi, M. R., & Jafarzadeh, A. H. (2013). A supplier selection method using ar-dea and fuzzy vikor, International Journal of Industrial Engineering, 20(5), 387-400.
    11.
  11. Chaghooshi, A. J., Fathi, M. R., Faghih, A., & Zarchi, M. K. (2012). Applying a New Integration of MCDM Techniques for Supplier Selection (Case Study: Pars Tire Company), Australian Journal of Basic and Applied Sciences, 6(2), 9-19.
    12.
  12. Chaghooshi, A., Fathi, M. R., Avazpour, R., & Ebrahimi, E. (2014). A Combined Approach for Supplier Selection: Fuzzy AHP and Fuzzy VIKOR, International Journal of Engineering Sciences, 3(8), 67-74.
    13.
  13. Safari, H., Fagheyi, M. S., Ahangari, S. S., & Fathi, M. R. (2012). Applying Promethee method based on entropy weight for supplier selection, Business management and strategy, 3(1), 97-106.
    14.
  14. Chen, C. T., Lin, C. T., & Huang, S. F. (2006). A fuzzy approach for supplier evaluation and selection in supply chain management, International journal of production economics, 102(2), 289-301.
    15.
  15. Rajesh, R., & Ravi, V. (2015). Supplier selection in resilient supply chains: a grey relational analysis approach, Journal of Cleaner Production, 86, 343-359.
    16.
  16. Wang, Y. X., (2005). Application of fuzzy decision optimum model in selecting supplier, The Journal of Science Technology and Engineering 5(15), 1100-1103.
    17.
  17. Yang, C. C., Chen, B. S. (2006). Supplier selection using combined analytical hierarchy process and grey relational analysis, Journal of Manufacturing Technology Management, 17(7), 926-941.
    18.
  18. Li, G. D., Yamaguchi, D., Nagai, M. (2007). A grey-based decision-making approach to the supplier selection problem, Mathematical and computer modelling, 46(3), 573-581.
    19.
  19. Demirtas, E. A., Üstün, Ö. (2008). An integrated multiobjective decision making process for supplier selection and order allocation, Omega, 36(1), 76-90.
    20.
  20. Wu, D. (2009). Supplier selection: A hybrid model using DEA, decision tree and neural network, Expert Systems with Applications, 36(5), 9105-9112.
    21.
  21. Boran, F. E., Genç, S., Kurt, M., Akay, D. (2009). A multicriteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method, Expert Systems with Applications, 36(8), 11363-11368.
    22.
  22. Kokangul, A., Susuz, Z. (2009). Integrated analytical hierarch process and mathematical programming to supplier selection problem with quantity discount, Applied mathematical modelling, 33(3), 1417-1429.
    23.
  23. Thanaraksakul, W., Phruksaphanrat, B. (2009). Supplier evaluation framework based on balanced scorecard with integrated corporate social responsibility perspective, Proceedings of the International MultiConference of Engineers and Computer Scientists, 2, 5-10.
    24.
  24. Vinodh, S., Anesh Ramiya, R., Gautham, S. G. (2011). Application of fuzzy analytic network process for supplier selection in a manufacturing organisation, Expert Systems with Applications, 38(1), 272-280.
    25.
  25. Golmohammadi, D., Mellat-Parast, M. (2012). Developing a grey-based decision-making model for supplier selection, International Journal of Production Economics, 137(2), 191-200.
    26.
  26. Brauers, W. K. M., & Zavadskas, E. K. (2006). The MOORA method and its application to privatization in a transition economy, Control and Cybernetics, 35(2), 445–469.
    27.
  27. Brauers, W. K. M., & Zavadskas, E. K. (2010a). Project management by MULTIMOORA as an instrument for transition economies, Technological and Economic Development of Economy, 16(1), 5–24.
    28.
  28. Brauers, W. K. M., Balezˇentis, A., & Balezˇentis, T. (2011). MULTIMOORA for the EU Member States updated with fuzzy number theory, Technological and Economic Development of Economy, 17(2), 259–290.
    29.
  29. Baležentis, A., Baležentis, T., & Brauers, W. K. (2012). Personnel selection based on computing with words and fuzzy MULTIMOORA, Expert Systems with Applications, 39(9), 7961-7967.
    30.


 

 

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