Advertisement

Journal of Intelligent Manufacturing

, Volume 30, Issue 1, pp 207–228 | Cite as

A hybrid ensemble and AHP approach for resilient supplier selection

  • Seyedmohsen HosseiniEmail author
  • Abdullah Al Khaled
Article

Abstract

Suppliers play a crucial role in achieving the supply chain goals. In the context of risk management, suppliers are the most common source of external risks in modern supply chains. The recognition that continuity of supply chain flow under disruptive event is a critical issue has brought the attention of companies to the selection of resilient suppliers. In contrast to the extensive number of researches on traditional and green criteria of supplier selection, the criteria associated with resilient supplier selection are not well explored yet. This paper first seeks to explore the resilience criteria for supplier selection based on the notion of resilience capacities which can be divided into three categories: absorptive capacity, adaptive capacity, and restorative capacity. Absorptive capacity refers to the capability of system to withstand against disruptive event in prior or called as preparedness of supplier, while adaptive and restoration capacities imply the capability of supplier to adopt itself and restore from disruption or recoverability of supplier. We identified eight effective elements for resilience capacities which contribute to the resilience of suppliers. Advanced data mining approaches like predictive analytics models are used to predict the resilience value of each supplier. We applied ensemble methods by combining binomial logistics regression, classification and regression trees, and neural network to obtain better predictive performance than individual algorithm from the historical data to predict individual supplier’s resiliency. This resilience value, obtained from ensemble methods, is coupled with additional four variables to assess the suppliers’ overall performance and rank them using different supplier selection models. Finally, a case study has been performed on international plastic raw material suppliers for a U.S. based manufacturer.

Notes

Acknowledgments

The authors are grateful to the anonymous reviewers for their insightful comments and suggestions which notably helped to improve the quality of this paper.

References

  1. Abdollahi, M., Arvan, M., & Razmi, J. (2015). An integrated approach for supplier portfolio selection: Lean or agile? Expert Systems with Applications., 42, 679–690.Google Scholar
  2. Al Khaled, A., & Hosseini, S. (2015). Fuzzy adaptive imperialist competitive algorithm for global optimization. Neural Computing and Applications, 26(4), 813–825.Google Scholar
  3. American Society of Mechanical Engineers (ASME). (2009). Innovative Technological Institute (ITI). Washington, D.C.: ASME ITI LLC.Google Scholar
  4. Arikan, F. (2013). A fuzzy solution approach for multi objective supplier selection. Expert Systems with Applications., 40, 947–952.Google Scholar
  5. Bhamra, R., Dani, S., & Burnard, K. (2011). Resilience: The concept, a literature review and future directions. International Journal of Production Research., 49(18), 5375–5393.Google Scholar
  6. Buyukozkan, G., & Cifci, G. (2012). A novel hybrid MCDM approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS to evaluate green suppliers. Expert System with Applications, 39, 3000–3011.Google Scholar
  7. Chan, F. T. S., Chan, H. K., & IP, R. W. L., & Lau, H. C. W., (2007). A decision support system for supplier selection in the airline industry. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacturer, 221(4), 741–758.Google Scholar
  8. Chen, C. H., Tan, H. K., Liao, L. R., Chen, H. H., Chan, C. C., Cheng, J. J., et al. (2007). Long-term psychological outcome of 1999 Taiwan earthquake survivors: A survey of a high-risk sample with property damage. Comprehensive Psychiatry., 48(3), 269–275.Google Scholar
  9. Chiou, C., Hsu, C., & Hwang, W. (2008). Comparative investigation on green supplier selection of the America, Japanese and Taiwanese electronics industry in China. IEEE International Conference on Industrial Engineering and Engineering Management, IEEM, 2008, (pp. 1909–1914).Google Scholar
  10. Cho, G., Kim, J., Ho Park, H., Noh, C.-S., So, S.-H., Park, Y. S., & Jung, K.H. (2008). An optimal decision making model for supplier and buyer’s win-win strategy in a two echelon supply chain. Proceeding of the \(41^{\rm st}\) Hawaii International Conference on System Sciences, 7–10 January 2008 (pp. 1–12). Big Island, HI, USA: Waikoloa.Google Scholar
  11. Choudhary, D., & Shankar, R. (2013). Joint decision of procurement lot-size, supplier selection, and carrier selection. Journal of Purchasing & Supply Management, 19, 16–26.Google Scholar
  12. Christopher, M., & Lee, H. (2004). Mitigating supply chain risk through improved confidence. International Journal of Physical Distribution & Logistics management, 34(5), 388–396.Google Scholar
  13. Dalalah, D., Hayajneh, M., & Batieha, F. (2011). A fuzzy multi-criteria decision making model for supplier selection. Expert Systems with Applications, 38(7), 8384–8391.Google Scholar
  14. Deng, X., Hu, Y., Deng, Y., & Mahadevan, S. (2014). Supplier selection using AHP methodology extended by D numbers. Expert Systems with Applications, 41, 156–167.Google Scholar
  15. Deng, Y., & Chen, F. T. S. (2011). A new fuzzy dempster MCDM method and its application in supplier selection. Expert Systems with Applications, 38(8), 9854–9861.Google Scholar
  16. Du, B., Guo, S., Huang, X., & Guo, J. (2015). A Pareto supplier selection algorithm for minimum the life cycle cost of complex product system. Expert Systems with Applications, 42, 4253–4264.Google Scholar
  17. Fazlollahtabar, H., Mahdavi, I., Talebi Ashoori, M., Kaviani, S., & Mahdavi-Amiri, N. (2011). A multi-objective decision making process of supplier selection and order allocation for multi-period scheduling in an electronic market. International Journal of Advanced manufacturing Technology, 52, 1039–1052.Google Scholar
  18. Farzipoor Saen, R. (2007). Suppliers selection in the presence of both cardinal and ordinal data. European Journal of Operational Research, 183, 741–747.Google Scholar
  19. Gencer, C., & Gurpinar, D. (2007). Analytic network process in supplier selection: A case study in an electronic firm. Applied Mathematical Modelling, 31, 2475–2486.Google Scholar
  20. Grisi, R. M., Guerra, L., & Naviglio, G. (2010). Supplier performance evaluation for green supply chain management. In T. Paolo (Ed.), Business performance measurement and management (pp. 149–163). Berlin: Springer.Google Scholar
  21. Guneri, A. F., Ertay, T., & Yucel, A. (2011). An approach based on ANFIS input selection and modeling for supplier selection problem. Expert Systems with Applications, 38, 14907–14917.Google Scholar
  22. Hang Hong, G., Chan Park, S., Sik Jang, D., & Min Rho, H. (2005). An effective supplier selection method for constructing a competitive supply-relationship. Expert Systems with Applications, 28, 629–639.Google Scholar
  23. Hong-jun, L., & Bin., L. (2010). A research on supplier assesment indices system of green purchasing. 2010 International Conference on E-Business and E-government (ICEE). (pp 3335–3338) IEEE.Google Scholar
  24. Hosseini, S., & Al Khaled, A. (2014). A survey on the imperialist competitive algorithm metaheuristic: Implementation in engineering domain and directions for future research. Applied Soft Computing, 24, 1078–1094.Google Scholar
  25. Hsu, C.-W., Kuo, T.-C., Chen, S.-H., & Hu, A. H. (2013). Using DEMATEL to develop a carbon management model of supplier selection in green supply chain management. Journal of Cleaner production, 56, 164–172.Google Scholar
  26. Huang, S. H., & Keskar, H. (2007). Comprehensive and configurable metrics for supplier selection. International Journal of Production Economics, 105, 510–523.Google Scholar
  27. Humphreys, Y. W. (2003). Integrating environmental criteria into supplier selection process. Journal of Mechanical Processing Technology, 138, 349–356.Google Scholar
  28. Igarashi, M., De Boer, L., & Magerholm Fet, A. (2013). What is required for greener supplier selection? A literature review and conceptual model development. Journal of Purchasing & Supply Management, 19, 247–263.Google Scholar
  29. Igoulalene, I., Benyoucef, L., & Kumar Tiwari, M. (2015). Novel fuzzy hybrid multi-criteria decision making approaches for the strategic supplier selection problem. Expert Systems with Applications, 42, 3342–3356.Google Scholar
  30. Kahraman, C., & Kaya, I. (2010). Supplier selection in agile manufacturing using fuzzy AHP. In L. Wang & S. C. L. Koh (Eds.), Enterprise networks and logistics for agile manufacturing (pp. 155–190). New York: Springer.Google Scholar
  31. Kang, H.-Y., Lee, A. H. I., & Yang, C.-Y. (2010). A fuzzy ANP model for supplier selection as applied to IC packing. Journal of Intelligent Manufacturing, 23, 1477–1488.Google Scholar
  32. Karsak, E. E., & Dursun, M. (2014). An integrated supplier selection methodology incorporating QFD and DEA with imprecise data. Expert Systems with Applications, 41, 6995–7004.Google Scholar
  33. Kilincci, O., & Onal, S. A. (2011). Fuzzy AHP approach for supplier selection in a washing machine company. Expert Systems with Applications, 38, 9656–9664.Google Scholar
  34. Koivo, H. N. (2008). Neural Networks: Basic using MATLAB Neural Network Toolbox. http://staff.ttu.ee/~jmajak/Neural_networks_basics_.pdf.
  35. Kumar Kar, A. (2014). Revisiting the supplier selection problem: An integrated approach for group decision support. Expert Systems with Applications, 41, 2762–2771.Google Scholar
  36. Lee, J., Cho, H., & Kim, Y. S. (2014). Assessing business impacts of agility criterion and order allocation strategy in multi-criteria supplier selection. Expert Systems with Applications, 42(3), 1136–1148.Google Scholar
  37. Li, G.-D., Yamaguchi, D., & Nagai, M. (2008). A grey-based decision-making approach to supplier selection. International Journal of Advanced Manufacturing Technology, 36, 1032–1040.Google Scholar
  38. Liao, C.-N., & Kao, H.-P. (2011). An integrated fuzzy TOPSIS and MCGP approach to supplier selection in supply chain management. Expert Systems with Applications, 38, 10803–10811.Google Scholar
  39. Lienland, B., Baumgartner, A., & Kunbben, E. (2013). The undervaluation of corporate reputation as a supplier selection factor: An analysis of ingredient branding of complex products in the manufacturing industry. Journal of Purchasing & Supply Management, 19, 84–97.Google Scholar
  40. Luo, X., Rosenber, D., & Barnes, D. (2009). Supplier selection in agile supply chains: An information-processing model and illustration. Journal of Purchasing & Supply Management, 15, 249–262.Google Scholar
  41. Masi, D., Micheli, G. J. L., & Cagno, E. (2013). A meta-model for choosing a supplier selection technique within an EPC company. Journal of Purchasing & Supply Management, 19, 5–15.Google Scholar
  42. Manual, J. (2013). The long road to recovery: Environmental health impacts on hurricane sandy. Environmental Health Perspectives., 212, 152–159.Google Scholar
  43. Ozkok, B. A., & Tiryaki, F. (2011). A compensatory fuzzy approach to multi-objective supplier selection problem with multiple-item. Expert Systems with Applications, 38, 11363–11368.Google Scholar
  44. Papadakis, I. S. (2006). Financial performance of supply chains after disruptions: An event study. Supply Chain Management: An International Journal, 11(1), 25–33.Google Scholar
  45. Pettit, T. J., Fiksel, J., & Croxton, K. L. (2011). Ensuring supply chain resilience: Development of a conceptual framework. Journal of Business Logistics, 31, 1–21.Google Scholar
  46. Pi, W.-N., & Low, C. (2005). Supplier evaluation and selection using Taguchi loss functions. International Journal of Advanced Manufacturing Technology, 26, 155–160.Google Scholar
  47. Rajesh, R., & Ravi, V. (2015). Supplier selection in resilient supply chains: A grey relational analysis approach. Journal of Cleaner production, 86, 343–359.Google Scholar
  48. Rezaei, J., & Ortt, R. (2013). Supplier segmentation using fuzzy logic. Industrial Marketing Management, 42, 507–517.Google Scholar
  49. Saaty, T. L. (1980). The analytical hierarchy process: Planning, priority setting, resources allocation. New York: McGraw-Hill Inc.Google Scholar
  50. Sanayei, A., Mousavi, S. F., Abdi, M. R., & Mohaghar, A. (2008). An integrated group decision-making process for supplier selection and order allocation using multi-attribute utility theory and linear programming. Journal of the Franklin Institute., 345, 731–747.Google Scholar
  51. Sawik, T. (2013). Selection of resilient supply portfolio under disruption risks. Omega, 41, 259–269.Google Scholar
  52. Sen, S., Basligil, H., Sen, C. G., & Barali, H. (2008). A framework for defining both qualitative and quantitative supplier selection criteria considering the buyer-supplier integration strategies. International Journal of production Research, 46(7), 1825–1845.Google Scholar
  53. Sen, C. G., Basligil, H., Sen, S., & Baracli, H. (2009). An integrated decision support system dealing with qualitative and quantitative objectives for enterprise software selection. Expert Systems with Application, 36(3), 5272–5283.Google Scholar
  54. Sheffi, Y. (2006). Resilience reduces risk. Logistics Quarterly, 12(1), 12–14.Google Scholar
  55. Singh, A. (2014). Supplier evaluation and demand allocation among suppliers in a supply chain. Journal of Purchasing & Supply Management, 20, 167–176.Google Scholar
  56. Stueland, V.J. (2004). Supplier evaluations: best practices and creating or improving your own evaluation, Wells Fargo Services Company. Proceeding of 89th Annual International Supply Management Conference.Google Scholar
  57. Torabi, S. A., Baghersad, M., & Mansouri, S. A. (2015). Resilient supplier selection and order allocation under operational and disruption risks. Transportation Research Part E, 79, 22–48.Google Scholar
  58. Toloo, M., & Nalchigar, S. (2011). A new DEA method for supplier selection in presence of both cardinal and ordinal data. Expert Systems with Applications., 38, 14726–14731.Google Scholar
  59. Wang, H. S., & Che, Z. H. (2007). An integrated model for supplier selection decisions in configuration changes. Expert Systems with Applications, 32, 1132–1140.Google Scholar
  60. Wu, D. D., Zhang, Y., Wu, D., & Olson, D. L. (2010). Fuzzy multiobjective programming for supplier selection and risk modeling: A possibility approach. European Journal of Operational Research., 200(3), 774–787.Google Scholar
  61. WWW resource 2. http://www.alibaba.com
  62. You, X.-Y., You, J.-X., Liu, H.-C., & Zhen, L. (2015). Group multi-criteria supplier selection using an extended VIKOR method with interval 2-tuple linguistic information. Expert Systems with Applications, 42, 1906–1916.Google Scholar
  63. Zsidisin, G. A., & Smith, M. E. (2005). Managing supply risk with early supplier involvement: A case study and research propositions. Journal of Supply Chain Management., 41(4), 44–57.Google Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.School of Industrial and Systems EngineeringUniversity of OklahomaNormanUSA
  2. 2.Influence HealthBirminghamUSA

Personalised recommendations