Skip to main content
SpringerLink
Log in

Supplier selection using extended IT2 fuzzy TOPSIS and IT2 fuzzy MOORA considering subjective and objective factors

  • Methodologies and Application
  • Published:
Soft Computing Aims and scope Submit manuscript

Abstract

During recent years, determination of efficient supplier has become a major challenge for improving the organizational efficiency. However, determination of suitable suppliers is always a complex multiple criteria decision-making (MCDM) problem because it involves the consideration of a large number of objective and subjective factors and also the factors may be uncertain and conflict in nature. This paper presents two novel MCDM techniques in interval type-2 fuzzy (IT2F) environment capable of handling uncertain subjective and objective factors simultaneously for selection of efficient suppliers in real-life applications. Technique for order preference by similarity to the ideal solution (TOPSIS) and multi-objective optimization on the basis of ratio analysis (MOORA) methods are used in IT2F environment to evaluate subjective factors with regard to subjective factor measures (SFM), and traditional normalization technique is used to evaluate the objective factors in terms of objective factor measures (OFMs). Then, SFM and OFM are used to calculate supplier selection index (SSI) by using Brown and Gibson model. The proposed models are then demonstrated with a case study in an Indian manufacturing organization for selection of efficient suppliers. Sensitivity analysis and comparative study of the results are carried out. It is found that the model is useful and efficient for decision making and evaluation of suitable suppliers in an uncertain environment.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  • Amid A, Ghodsypour SH, O’brien C (2006) Fuzzy multiobjective linear model for supplier selection in a supply chain. Int J Prod Econ 104(2):394–407

    Article  Google Scholar 

  • Amin SH, Zhang G (2012) A proposed mathematical model for closed-loop network configuration based on product life cycle. Int J Adv Manuf Technol 58(5):791–801

    Article  Google Scholar 

  • Arikan F (2015) An interactive solution approach for multiple objective supplier selection problem with fuzzy parameters. J Intell Manuf 26(5):989–998

    Article  Google Scholar 

  • Asadabadi MR (2014) A hybrid QFD-based approach in addressing supplier selection problem in product improvement process. Int J Ind Eng Comput 5(4):543–560

    Google Scholar 

  • Bera AK, Jana DK (2017) Multi-item imperfect production inventory model in bi-fuzzy environments. OPSEARCH 54(2):260–282

    Article  MathSciNet  MATH  Google Scholar 

  • Brauers WKM (2004) Optimization methods for a stakeholder society. A revolution in economic thinking by multiobjective optimization: non-convex optimization and its applications. Kluwer Academic Publishers, Boston

    Book  MATH  Google Scholar 

  • Brown PA, Gibson DF (1972) A quantified model for facility site selection application to multi plant location problem. AIIE Trans 4(1):1–10

    Article  Google Scholar 

  • Chen SJ, Hwang CL (1992) Fuzzy multi attribute decision making, vol 375 of Lecture notes in economics and mathematical system. Springer, New York

    Google Scholar 

  • Chen SM, Lee LW (2010) Fuzzy multiple attributes group decision-making based on the interval type-2 TOPSIS method. Expert Syst Appl 37(4):2790–2798

    Article  Google Scholar 

  • Chen CT, Lin CT, Huang SF (2006) A fuzzy approach for supplier evaluation and selection in supply chain arrangement. Int J Prod Econ 102(2):289–301

    Article  Google Scholar 

  • Dickson GW (1966) An analysis of vendor selection systems and decisions. J Purch 2(1):5–17

    Article  Google Scholar 

  • Elanchezhian C, Ramnath BV, Kesavan R (2010) Vendor evaluation using multicriteria decision making technique. Int J Comput Appl 5(9):4–9

    Google Scholar 

  • Ellram LM (1990) The supplier selection decision in strategic partnerships. J Purch Mater Manag 26(4):8–14

    Google Scholar 

  • Farrokh M, Kassaee M, Nia HH (2013) An integrated hybrid MCDM approach for vendor selection problem. Bus Manag Horiz 1(1):153–170

    Article  Google Scholar 

  • Ha SH, Krishnan R (2008) A hybrid approach to supplier selection for the maintenance of a competitive supply chain. Expert Syst Appl 34(2):1303–1311

    Article  Google Scholar 

  • Haldar A, Ray A, Banerjee D, Ghosh S (2012) A hybrid MCDM model for resilient supplier selection. Int J Manag Sci Eng Manag 7(4):284–292

    Google Scholar 

  • Handfield R, Walton SV, Sroufe R, Melnyk SA (2002) Applying environmental criteria to supplier assessment: a study in the application of the analytical hierarchy process. Eur J Oper Res 141(1):70–87

    Article  MATH  Google Scholar 

  • Hisdal E (1981) The IF THEN ELSE statement and interval-valued fuzzy sets of higher type. Int J Man Mach Stud 15(4):385–455

    Article  MathSciNet  MATH  Google Scholar 

  • Ho W, Xu X, Dey PK (2010) Multi-criteria decision making approaches for supplier evaluation and selection: a literature review. Eur J Oper Res 202(1):16–24

    Article  MATH  Google Scholar 

  • John RI (1998) Type 2 fuzzy sets: an appraisal of theory and applications. Int J Uncertain Fuzziness Knowl-Based Syst 6(6):563–576

    Article  MathSciNet  MATH  Google Scholar 

  • Karnik NN, Mendel JM (2001) Operations on type-2 fuzzy sets. Fuzzy Sets Syst 122(2):327–348

    Article  MathSciNet  MATH  Google Scholar 

  • Kilincci O, Onal SA (2011) Fuzzy AHP approach for supplier selection in a washing machine company. Expert Syst Appl 38(8):9656–9664

    Article  Google Scholar 

  • Krajewsld LJ, Ritzman LP (1996) Operations management strategy and analysis. Addison-Wesley Publishing Co, London

    Google Scholar 

  • Kulak O, Durmusoglu B, Kahraman C (2005) Fuzzy multi-attribute equipment selection based on information axiom. J Mater Process Technol 169(3):337–345

    Article  Google Scholar 

  • Labib AW (2011) A supplier selection model: a comparison of fuzzy logic and the analytic hierarchy process. Int J Prod Res 49(21):6287–6299

    Article  Google Scholar 

  • Lee LW, Chen SM (2008) Fuzzy multiple attributes group decision-making based on the extension of TOPSIS method and interval type-2 fuzzy sets. In: Proceedings of the seventh international conference on machine learning and cybernetics. IEEE, pp 3260–3265

  • Li CC, Fun YP, Hung JS (1997) A new measure for supplier performance evaluation. IIE Trans Oper Eng 29(9):753–758

    Google Scholar 

  • Liu FHF, Hai HL (2005) The voting analytic hierarchy process method for selecting supplier. Int J Prod Econ 97(3):308–317

    Article  Google Scholar 

  • Mendel JM (2007) Advances in type-2 fuzzy sets and systems. Inf Sci 177(1):84–110

    Article  MathSciNet  MATH  Google Scholar 

  • Mendel JM, John RI, Liu FL (2006) Interval type-2 fuzzy logical systems made simple. IEEE Trans Fuzzy Syst 14(6):808–821

    Article  Google Scholar 

  • Mohammadshahi Y (2013) A state-of-art survey on TQM applications using MCDM techniques. Decis Sci Lett 2(3):125–134

    Article  Google Scholar 

  • Otheman A, Ghani ATA, Abdullah L (2014) The use of interval type-2 fuzzy TOPSIS in supplier selection. Appl Mech Mater 548:1954–1958

    Article  Google Scholar 

  • Pal OM, Gupta AK, Garg RK (2013) Supplier selection criteria and methods in supply chains: a review. Int J Econ Manag Eng 7(10):173–179

    Google Scholar 

  • Setiawan H, Anggi GD, Bambang PKB (2013) Application of analytic network process in the performance evaluation of local black-soybean supply to Unilever Indonesia’s soy-sauce product. In: International symposium on analytic hierarchy process, pp 1–10

  • Tahriri F, Osman MR, Ali A, Yusuff RM, Esfandiary A (2008) AHP approach for supplier evaluation and selection in a steel manufacturing company. J Ind Eng Manag 1(2):54–76

    Google Scholar 

  • Turk S, John R, Ozcan E (2014) Interval type-2 fuzzy sets in supplier selection. In: 14th UK Working on Computing Intelligence. IEEE, pp 1–7

  • Wang JW, Cheng CH, Huang KC (2009) Fuzzy hierarchical TOPSIS for supplier selection. Appl Soft Comput 9(1):377–386

    Article  Google Scholar 

  • Weber CA, Current JR, Benton WC (1991) Vendor selection criteria and methods. Eur J Oper Res 50(1):2–18

    Article  MATH  Google Scholar 

  • Zadeh LA (1965) Fuzzy sets. Inf Control 8:338–353

    Article  MATH  Google Scholar 

  • Zadeh LA (1975) The concept of a linguistic variable and its application to approximate reasoning—1. Inf Sci 8(3):199–249

    Article  MathSciNet  MATH  Google Scholar 

  • Zamri N, Abdullah LA (2014) A new positive and negative linguistic variable of interval triangular type-2 fuzzy sets for MCDM. In: Recent advances on soft computing and data mining. Springer, Cham, pp 69–78. https://doi.org/10.1007/978-3-319-07692-8_7

  • Zamri N, Abdullah LA (2015) A new aggregating phase for interval type-2 fuzzy TOPSIS using the ELECTRE I method. In: Advanced computer and communication engineering technology. Springer, Cham, pp 873–881. https://doi.org/10.1007/978-3-319-07674-4_82

  • Zeydan M, Colpan C, Cobanoglu C (2011) A combined methodology for supplier selection and performance evaluation. Expert Syst Appl 38(3):2741–2751

    Article  Google Scholar 

Download references

Acknowledgements

We declared that research work was done by self-finance. No institutional fund has been provided.

Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, Haldia Institue of Technology, Haldia, Purba Midnapur, West Bengal, 721657, India

    Ashoke Kumar Bera

  2. Department of Applied Science, Haldia Institute of Technology, Haldia, Purba Midnapur, West Bengal, 721657, India

    Dipak Kumar Jana

  3. Department of Production Engineering, Jadavpur University, Jadavpur, Kolkata, West Bengal, 700032, India

    Debamalya Banerjee

  4. Department of Mechanical Engineering, Jadavpur University, Jadavpur, Kolkata, West Bengal, 700032, India

    Titas Nandy

Authors
  1. Ashoke Kumar Bera
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dipak Kumar Jana
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Debamalya Banerjee
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Titas Nandy
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Dipak Kumar Jana.

Ethics declarations

Conflict of interest

The authors have no conflict of interest for the publication of this paper.

Human participants or animals

The authors declared that this article does not contain any studies with human participants or animals performed by any of the authors.

Additional information

Communicated by V. Loia.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bera, A.K., Jana, D.K., Banerjee, D. et al. Supplier selection using extended IT2 fuzzy TOPSIS and IT2 fuzzy MOORA considering subjective and objective factors. Soft Comput 24, 8899–8915 (2020). https://doi.org/10.1007/s00500-019-04419-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00500-019-04419-z

Keywords

Search

Navigation