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A Combination of Analytic Hierarchy Process Method and Machine Learning for Supplier Selection in Supply Chain Management

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Proceedings of the 4th International Conference on Research in Management and Technovation (ICRMAT 2023)

Abstract

Selecting the right list of supplier is a critical activity in the supply chain management system. The supplier selection process is one of the important decision-making tasks of managers. The supplier selection process is often integrated in the supply chain information system to help businesses make the final choices for a list of the most suitable suppliers for the business. In this work, a combination between AHP method and machine learning is used via proposal framework. This framework is performed with experimental data to show the support managers’ decision making through the short risky list suppliers. This might help each enterprise in the industry having their own suitable suppliers. This framework also makes a transparency of selecting suppliers in the supply chain system in order to create the competitiveness on product prices for businesses in the market.

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References

  1. Baryannis, G., Dani, S., Validi, S., Antoniou, G.: Decision Support Systems and Artificial Intelligence in Supply Chain Risk Management, in Revisiting Supply Chain Risk. Springer Series in Supply Chain Management, pp. 53–71. Springer (2019)

    Google Scholar 

  2. Chai, J., Ngai,W.T.: Decision-making techniques in supplier selection: recent accomplishments and what lies ahead. Expert Syst. Appl. 140 (2020)

    Google Scholar 

  3. Constante-Nicolalde, F.-V., Guerra-Terán, P., Pérez-Medina, J.-L.: Fraud prediction in smart supply chains using machine learning techniques. In: Applied Technologies, vol. 1194, pp. 145–159. Springer (2020)

    Google Scholar 

  4. Hasan, K., Asil, O., Angappa, G., Ferhan, C.: An integrated decision analytic framework of machine learning with multi-criteria decision making for multi-attribute inventory classification. Comput. Ind. Eng. 101(C), 599–613 (2016)

    Google Scholar 

  5. 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)

    Article  Google Scholar 

  6. Lakshmanpriya, C., Sangeetha, N., Lavanpriya, C.: Vendor selection in manufacturing industry using AHP and ANN. SIJ Trans. Ind. Financial Bus. Manage. 1(1), 29–34 (2013)

    Google Scholar 

  7. Mohamed-Iliasse, M., Loubna, B., Abdelaziz, B.: Machine learning in supply chain management: a systematic literature review. Int. J. Supply Oper. Manage. (IJSOM) 9(4), 398–416 (2022)

    Google Scholar 

  8. Nhu-Mai, T.N., Phong, T.H.: Criteria for supplier selection in textile and apparel industry: a case study in Vietnam. J. Asian Finance Econ. Bus. 6(2), 213–221 (2019)

    Article  Google Scholar 

  9. Quinlan, J.R.: Induction of decision trees. Mach. Learn. 1(1), 81–106 (1986)

    Article  Google Scholar 

  10. Saaty, T.: The Analytic Hierarchy Process. McGraw-Hill (1980)

    Google Scholar 

  11. Saaty, T.L.: Decision making with the analytic hierarchy process. Int. J. Serv. Sci. 1(1), 83–98 (2008)

    Google Scholar 

  12. Schroeder, M., Lodemann, S.: A systematic investigation of the integration of machine learning into supply chain risk management. Logistics. 5(3), 62 (2021)

    Article  Google Scholar 

  13. Shannon, C.E., Weaver, W.: The Mathematical Theory of Communication. University of Illinois Press (1949)

    Google Scholar 

  14. Tang, S., Hakim, N., Khaksar, W., Ariffin, M., Sulaiman, S., Pah, P.: A hybrid method using analytic hierarchical process and artificial neural network for supplier selection. Int. J. Innov. Manage. Technol. 4(1), 109–111 (2013)

    Google Scholar 

  15. Tirkolaee, E.B., Sadeghi, S., Mooseloo F.M., Vandchali, H.R., Aeini, S.: Application of Machine Learning in Supply Chain Management: A Comprehensive Overview of the Main Areas. Machine Learning in Sustainable Industrial Development, vol. 2021 (2021)

    Google Scholar 

  16. Velasquez, M., Hester, P.T.: An analysis of multi-criteria decision making methods. Int. J. Oper. Res. 10(2), 56–66 (2013)

    Google Scholar 

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Correspondence to Thuy Nguyen Thi Thu .

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Thu, T.N.T., Chi, T.N., Maidin, S.S. (2024). A Combination of Analytic Hierarchy Process Method and Machine Learning for Supplier Selection in Supply Chain Management. In: Nguyen, T.H.N., Burrell, D.N., Solanki, V.K., Mai, N.A. (eds) Proceedings of the 4th International Conference on Research in Management and Technovation. ICRMAT 2023. Springer, Singapore. https://doi.org/10.1007/978-981-99-8472-5_5

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