Fuzzy TOPSIS and Grey Relation Analysis Integration for Supplier Selection in Fiber Industry

Document Type : Research Paper

Authors

1 Department of Mechanical Engineering, Agnel Institute of Technology and Design, Assagao, Bardez-Goa, India

2 Department of Mechanical Engineering, Sahyadri College of Egineering and Management, Manglore, Affiliated to Visvesvarya Technological University, Belagavi, India

3 Department of Mechanical Engineering, PES Institute of Technology and Management, Shivamogga, Affiliated to Visvesvarya Technological University, Belagavi, India

4 Department of Mechanical Engineering, BVVS Polytechnic, Bagalkot, Kar nataka, India

Abstract

In the present work, selection of right corrugated box supplier for fibre industry is studied. Decision makers independently evaluate the supplier’s strength for both qualitative (quality, reliability, flexibility, stability, capability, and availability) and quantitative (order volume, price, delivery, credit period and location) criteria’s with conflict in nature. Inappropriate choice of supplier by traditional approach could result in financial losses. Hybrid approach (Fuzzy TOPSIS and Grey relational analysis GRA) is proposed to select the right corrugated box supplier from the pool of suppliers for Fiber industry located in Goa, India. Fuzzy TOPSIS method is applied to evaluate the qualitative criteria, whereas, GRA for quantitative criteria’s for selecting the best supplier. Considering the ranks obtained from both the qualitative and quantitative criteria’s evaluated by Fuzzy TOPSIS and GRA, the best supplier is selected. In addition, sensitivity analysis is performed to know the changes in rank of suppliers with variation in preferential weights assigned to qualitative and quantitative criterion.

Keywords


Argilaguet Montarelo, L., R. Glardon, and N. Zufferey. (2017). A global simulation-optimisation approach for inventory management in a decentralised supply chain. Supply Chain Forum: An International Journal, Vol. 18(2), pp. 112-119.
Azadi, M., M. Jafarian, R. F. Saen, and S. M. Mirhedayatian. (2015). A new fuzzy DEA model for evaluation of efficiency and effectiveness of suppliers in sustainable supply chain management context. Computers & Operations Research, Vol.  54, pp. 274-285.
Azimifard, A., S. H. Moosavirad, and S. Ariafar. (2018). Selecting sustainable supplier countries for Iran's steel industry at three levels by using AHP and TOPSIS methods. Resources Policy, Vol. 57, pp. 30-44.
Badiezadeh, T., R. F. Saen, and T. Samavati. (2018). Assessing sustainability of supply chains by double frontier network DEA: A big data approach. Computers & Operations Research, Vol. 98, pp. 284-290.
Borade, A. B., and S. C. Bansod. (2011). Comparison of neural network-based forecasting methods using multi-criteria decision-making tools. Supply Chain Forum: An International Journal, Vol. 12(4), pp. 4-14.
Carrera, D. A., R. V. Mayorga, and W. Peng. (2020). A Soft Computing Approach for group decision making: A supply chain management application. Applied Soft Computing, in press. 106201. https://doi.org/10.1016/j.asoc.2020.106201
Chai, J., and E. W. Ngai, (2016). Decision model for complex group argumentation. Expert Systems with Applications, Vol. 45, pp. 223-233.
Chai, J., and E. W. Ngai, (2020). Decision-making techniques in supplier selection: Recent accomplishments and what lies ahead. Expert Systems with Applications, Vol. 140, in press. 112903. https://doi.org/10.1016/j.eswa.2019.112903
Chai, J., J. N. Liu, and E. W. Ngai. (2013). Application of decision-making techniques in supplier selection: A systematic review of literature. Expert Systems with Applications, Vol. 40(10), pp. 3872-3885.
Chen, S. J., and C. L. Hwang, (1992). Fuzzy multiple attribute decision-making methods. In Fuzzy multiple attribute decision-making. In: Fuzzy Multiple Attribute Decision Making. Lecture Notes in Economics and Mathematical Systems, Vol. 375. pp. 289-486. Springer, Berlin, Heidelberg.
Deng, J. L. (1982). Control problems of grey system. Systems and Control Letters, Vol. 1, pp. 288–294.
Dickson, G. W. (1966). An analysis of vendor selection systems and decisions. Journal of Purchasing , Vol. 2(1), pp. 5-17.
Ghassemi, A., J. Asl-Najafi, and S. Yaghoubi, (2018). A dynamic bi-objective closed-loop supply chain network design considering supplier selection and remanufacturer subcontractors. Uncertain Supply Chain Management, Vol. 6(2), pp. 117-134.
Ghayebloo, S., M. J. Tarokh, U. Venkatadri, and C. Diallo, (2015). Developing a bi-objective model of the closed-loop supply chain network with green supplier selection and disassembly of products: the impact of parts reliability and product greenness on the recovery network. Journal of Manufacturing Systems, Vol. 36, pp. 76-86.
Ghodsypour, S. H., and C. O’brien, (2001). The total cost of logistics in supplier selection, under conditions of multiple sourcing, multiple criteria and capacity constraint. International Journal of Production Economics, Vol. 73(1), pp. 15-27.
Govindan K, M. Kadziński, and R. Sivakumar, (2017). Application of a novel PROMETHEE-based method for construction of a group compromise ranking to prioritization of green suppliers in food supply chain. Omega, Vol. 71, pp. 129-145.
Ko, M., A. Tiwari, and J. Mehnen, (2010). A review of soft computing applications in supply chain management. Applied Soft Computing, Vol. 10(3), pp. 661-674.
Kogan, K., and C. S. Tapiero, (2007). Supply chain games: operations management and risk valuation (Vol. 113). Springer Science & Business Media.
Liao, C. N., and H. P. Kao, (2011). An integrated fuzzy TOPSIS and MCGP approach to supplier selection in supply chain management. Expert Systems with Applications, Vol. 38(9), pp. 10803-10811.
Luthra, S., K. Govindan, and S. K. Mangla, (2017b). Structural model for sustainable consumption and production adoption—A grey-DEMATEL based approach. Resources, Conservation and Recycling, Vol. 125, pp. 198-207.
Luthra, S., K. Govindan, D. Kannan, S. K. Mangla, and C. P. Garg, (2017a). An integrated framework for sustainable supplier selection and evaluation in supply chains. Journal of Cleaner Production, Vol. 140, pp.1686-1698.
Markabi, M. S., and M. Sabbagh, (2014). A hybrid method of GRA and DEA for evaluating and selecting efficient suppliers plus a novel ranking method for grey numbers. Journal of Industrial Engineering and Management, Vol. 7(5), pp.1197-1221.
Ortiz‐Barrios, M., C. Miranda‐De la Hoz, P. López‐Meza, A. Petrillo, and F. De Felice, (2020). A case of food supply chain management with AHP, DEMATEL, and TOPSIS. Journal of Multi‐Criteria Decision Analysis, Vol. 27(1-2), pp. 104-128.
Patil, A. N. (2014). Modern evolution in supplier selection criteria and method. International Journal of Management Research and Reviews, Vol. 4(5), pp. 616 -623.
Roshandel, J., S. S. Miri-Nargesi, and L. Hatami-Shirkouhi, (2013). Evaluating and selecting the supplier in detergent production industry using hierarchical fuzzy TOPSIS. Applied Mathematical Modelling, Vol. 37(24), pp. 10170-10181.
Sandeep, M., S. Kumanan, and S. Vinodh, (2011). Supplier selection using combined AHP and GRA for a pump manufacturing industry. International Journal of Logistics Systems and Management, Vol. 10(1), pp. 40-52.
Seker, S., F. Recal, and H. Basligil, (2017). A combined DEMATEL and grey system theory approach for analyzing occupational risks: A case study in Turkish shipbuilding industry. Human and Ecological Risk Assessment: An International Journal, Vol. 23(6), pp. 1340-1372.
Setak, M., S. Sharifi, and A. Alimohammadian, (2012). Supplier selection and order allocation models in supply chain management: A review. World Applied Sciences Journal, Vol. 18(1), pp. 55-72.
Yu, Q., and F. Hou, (2016). An approach for green supplier selection in the automobile manufacturing industry. Kybernetes, Vol. 45(4), pp. 571-588.