Supplier selection using Fuzzy AHP and Fuzzy Vikor for XYZ Pharmaceutical Manufacturing Company

  • Ruzanita Mat Rani Centre of Statistical and Decision Sciences Studies, Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia
  • Ahmad Fakhry Nadar Centre of Statistical and Decision Sciences Studies, Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia
Keywords: Fuzzy AHP, Fuzzy Vikor, Supplier Selection

Abstract

Supplier selection is not an easy process as it typically involves multiple criteria and it requires human judgment. Therefore, there is a need to have a better system for supplier selection due to uncertainty and vagueness that exist in dealing with the multiple criteria decision making (MCDM) problem.  This study is aimed to identify the important criteria for the selection of the best pharmaceutical raw materials supplier for XYZ Pharmaceutical Manufacturing company by using Fuzzy Analytical Hierarchy Process (AHP) and Fuzzy VIKOR approaches. Furthermore, this paper also presents the comparison results between the two methods in determining the best supplier. Fuzzy theory was used since it provides a right tool to encounter the uncertainties and complexity of decision making environment. This study investigated eight alternative suppliers based on seven criteria evaluated by two decision makers from the company. This study has successfully identified the top three most important criteria for the selection of supplier, namely, Regulatory Compliance, Price, and Product Variety. This study highlighted that Regulatory Compliance is a new important criterion for the pharmaceutical company to consider in future supplier selection. Based on the alternative results of Fuzzy AHP, it was found that the top three most important supplier were A5, A3 and A1. While based on the alternative results of Fuzzy VIKOR, it showed that the top three most important supplier were A5, A3 and A7. The comparison results between the two methods have shown that the Fuzzy VIKOR method is more suited to the problem of supplier selection.

References

[1] Hsu, B. M., Chiang, C. Y., & Shu, M. H. (2010). Expert Systems with Applications, 37(9), 6192-6200.

[2] Oliver, R. L. (2014). Abingdon, UK: Routledge.

[3] Asadabadi, M. (2014). International Journal of Industrial Engineering Computations, 5(4), 543-560.

[4] Christopher, M., Payne, A., & Ballantyne, D. (2013). Butterworth-Heinemann: Oxford.

[5] Vovchenko, G. N., Holina, G. M., Orobinskiy, S. A., & Sichev, A. R. (2017). European Research Studies Journal, 20(1), 350-368.

[6] Khorasani, O., & Bafruei, M. K. (2011). International Journal of Academic Research, 3(1).

[7] Parameshwaran, R., Kumar, S. P., & Saravanakumar, K. (2015). Applied Soft Computing, 26, 31-41.

[8] Enyinda, C.I., Emika, D. (2010). Proceedings of ASBBS, Los Vegas, February 2010, Vol.17, No.1, pp.77-91

[9] Asamoah, D., Annan, J., & Nyarko, S. (2012). International Journal of Business and Management, 7(10), 49.

[10] Aguezzoul, A. (2014). Omega, 49, 69-78

[11] Beikkhakhian, Y., Javanmardi, M., Karbasian, M., & Khayambashi, B. (2015). Expert Systems with Applications, 42(15), 6224-6236.

[12] Ayhan, M. B. (2013). arXiv preprint arXiv:1311.2886.

[13] Liao, H., & Xu, Z. (2013). Fuzzy Optimization and Decision Making, 12(4), 373-392.
Published
2020-02-03
How to Cite
Mat Rani, R., & Nadar, A. F. (2020). Supplier selection using Fuzzy AHP and Fuzzy Vikor for XYZ Pharmaceutical Manufacturing Company. EDUCATUM Journal of Science, Mathematics and Technology, 7(1), 14-21. Retrieved from http://ejournal.upsi.edu.my/index.php/EJSMT/article/view/2374