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Manuscript ID : 538601 Visit : 201 Page: 62 - 74

Article Type: Original Research

Optimum supplier selection based on a hybrid MCDM approach: AHP-VIKOR

Subject Areas : Industrial Management

Armin Cheraghalipour 1 , Mohammad Mahdi Paydar 2 , Mostafa Hajiaghaei-Keshteli 3

1 - department of industrial engineering, university of science and technology of Mazandaran, Behshahr, Iran
2 - Assistant professor, department of industrial engineering, Babol Noshirvani University of Technology, Babol
3 - Assistant professor, department of industrial engineering, university of science and technology of Mazandaran, Behshahr

Received: 2017-08-12 Accepted : 2018-03-09 Published : 2018-03-01

Keywords:

Abstract :

In recent decades, the selection of suitable suppliers as one of the important issues in the field of supply chain management is considered. The evaluation and selection of the best suppliers need to make decisions based on different criteria. In this study, a hybrid MCDM approach consists of AHP and VIKOR methods has been proposed that at first paid to identify the most important criteria in the supplier selection based on previous studies and interviews with company executives. Then by using questionnaires, the paired comparisons of criteria and paired comparisons matrix of groups according to the views of managers and based on Analytic Hierarchy Process (AHP) is performed. Next, using a multi-criteria optimization technique (VIKOR), firm's suppliers are ranked. Furthermore, a case study in the automotive industry is applied to accumulate data for proposed framework. Finally, by identifying effective criteria, appropriate suppliers, and similarity of obtained results with other studies, the efficiency of the proposed model is proved.

References:


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_||_

  1. Abdollahi, M., Arvan, M., & Razmi, J. (2015). An integrated approach for supplier portfolio selection: Lean or agile? Expert Systems with Applications, 42(1): 679–690.
    2.
  2. Albayrak, E., & Erensal, Y. C. (2004). Using analytic hierarchy process (AHP) to improve human performance. An application of multiple criteria decision making problem. Journal of Intelligent Manufacturing, 15(1): 491–503.
    3.
  3. Bhattacharya, A., Sarkar, B., & Mukherjee, S. K. (2005). Integrating AHP with QFD for robot selection under requirement perspective. International Journal of Production Research, 43(17): 3671–3685.
    4.
  4. Chan, F. T. S. (2003). Interactive selection model for supplier selection process: an analytical hierarchy process approach. International Journal of Production Research, 41(15): 3549–3579.
    5.
  5. Cheraghalipour, A., Paydar, M. M., & Hajiaghaei-keshteli, M. (2017). An Integrated Approach for Collection Center Selection in Reverse Logistic. International Journal of Engineering, TRANSACTIONS A: Basics, 30(7): 1005–1016.
    6.
  6. Deng, X., Hu, Y., Deng, Y., & Mahadevan, S. (2014). Supplier selection using AHP methodology extended by D numbers. Expert Systems with Applications, 41(1): 156–167.
    7.
  7. Dickson, G. W. (1966). An analysis of vendor selection systems and decisions. Journal of Purchasing, 2(1): 5–17.
    8.
  8. Dweiri, F., Kumar, S., Khan, S. A., & Jain, V. (2016). Designing an integrated AHP based decision support system for supplier selection in automotive industry. Expert Systems with Applications, 62: 273–283.
    9.
  9. Esposito, E., & Passaro, R. (2009). Evolution of the supply chain in the Italian railway industry. Supply Chain Management: An International Journal, 14(4): 303–313.
    10.
  10. Fallahpour, A., Udoncy, E., Siti, O., & Musa, N. (2015). A hybrid model for supplier selection : integration of AHP and multi expression programming ( MEP ). Neural Computing and Applications. https://doi.org/10.1007/s00521-015-2078-6
    11.
  11. Feng, D., Chen, L., & Jiang, M. (2005). Vendor selection in supply chain system: An approach using fuzzy decision and AHP. China, International Conference on Services Systems and Services Management, 1(1): 1–10.
    12.
  12. Goffin, K., Szwejczewski, M., & New, C. (1997). Managing suppliers: when fewer can mean more. International Journal of Physical Distribution & Logistics Management, 27(7): 422–436.
    13.
  13. Gold, S., & Awasthi, A. (2015). Sustainable global supplier selection extended towards sustainability risks from (1+n)th tier suppliers using fuzzy AHP based approach. IFAC-PapersOnLine, 48(3): 966–971.
    14.
  14. Gonzaılez, M. E., Quesada, G., & Monge, C. A. M. (2004). Determining the importance of the supplier selection process in manufacturing: a case study. International Journal of Physical Distribution & Logistics Management, 34(6): 492–504.
    15.
  15. HA, S., & KRISHNAN, R. (2008). A hybrid approach to supplier selection for the maintenance of a competitive supply chain. Expert Systems with Applications, 34(2): 1303–1311.
    16.
  16. Jain, V., Kumar, A., Sumit, S., & Nittin, S. (2016). Supplier selection using fuzzy AHP and TOPSIS : a case study in the Indian automotive industry. Neural Computing and Applications. https://doi.org/10.1007/s00521-016-2533-z
    17.
  17. Mendoza, A. (2007). Effective methodologies for supplier selection and order quantity allocation. The Pennsylvania State University. the Graduate School.
    18.
  18. Önüt, S., Kara, S. S., & Işik, E. (2009). Long term supplier selection using a combined fuzzy MCDM approach: A case study for a telecommunication company. Expert Systems with Applications, 36(2): 3887–3895.
    19.
  19. Opricovic, S. (1998). Multicriteria Optimization of Civil Engineering Systems. Faculty of Civil Engineering, 2(1): 5–21.
    20.
  20. Saaty, T. L. (1980). The Analytic Hierarchy Process: Planning, priority setting, resource, allocation. In McGraw-Hill (pp. 1–11). New York.
    21.
  21. Sanayei, A., Mousavi, S. F., & Yazdankhah, A. (2010). Group decision making process for supplier selection with VIKOR under fuzzy environment. Expert Systems with Application, 37(1): 24–30.
    22.
  22. Scott, J., Ho, W., Dey, P. K., & Talluri, S. (2014). A decision support system for supplier selection and order allocation in stochastic, multi-stakeholder and multi-criteria environments. International Journal of Production Economics, 166(1): 226–237.
    23.
  23. Sepehriar, A., Eslamipoor, R., & Nobari, A. (2013). A new mixed fuzzy-LP method for selecting the best supplier using fuzzy group decision making. Neural Computing and Applications, 23(1): 345–352.
    24.
  24. Shemshadi, A., Toreihi, M., Shirazi, H., & Tarokh, M. J. (2011). Supplier selection based on supplier risk: An ANP and fuzzy TOPSIS approach. The Journal of Mathematics and Computer Science, 2(1): 159–275.
    25.
  25. Tadić, S., Zečević, S., & Krstić, M. (2014). A novel hybrid MCDM model based on fuzzy DEMATEL, fuzzy ANP and fuzzy VIKOR for city logistics concept selection. Expert Systems with Applications, 41(18): 8112–8128.
    26.
  26. Veni, K. K., Rajesh, R., & Pugazhendhi, S. (2012). Development of decision making model using integrated AHP and DEA for vendor selection. Procedia Engineering, 38(1): 3700–3708.
    27.
  27. Wang, G., Huang, S. H., & Dismukes, J. P. (2005). Manufacturing supply chain design and evaluation. International Journal of Advanced Manufacturing Technology, 25(1): 93–100.
    28.

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