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An analysis approach to handle uncertain multi-criteria group decision problems in the framework of interval type-2 fuzzy sets theory

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Abstract

Uncertainty is one of the most important aspects of any decision-making process. One of the tools lately used in uncertain decision making is interval type-2 fuzzy sets (IT2FSs). These sets unlike the traditional fuzzy sets have more flexibility in expressing uncertainty and can be applied in situations in which the level of vagueness is very high. Unfortunately, most of the recently published papers on this issue are concerned with extending the existing fuzzy decision-making methods to type-2 fuzzy environment and the improvements were mainly focused on improving the applied fuzzy tool from classic sets to type-2 fuzzy sets. This paper offers a new analysis approach in an uncertain decision-making process that has enhancements in areas of the soft computing. In other words, this paper introduces an IT2F-based approach that has several novelties. Firstly, the decision-making method presents a new approach in computing the decision makers’ weights. This approach gives ideas of each decision maker a weight based on the gathered judgments. Secondly, the approach employs the concept of relative preference relation to evaluate the importance of each criterion. Thirdly, a novel decision-making index is introduced to rank the alternatives. The application of this novel last aggregation method is illustrated through solving an existing example in the literature on e-waste recycling programs assessment in Sri Lanka.

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References

  1. Abdullah L, Zulkifli N (2015) Integration of fuzzy AHP and interval type-2 fuzzy DEMATEL: an application to human resource management. Expert Syst Appl 42(9):4397–4409

    Article  Google Scholar 

  2. Amaral TM, Costa AP (2014) Improving decision-making and management of hospital resources: an application of the PROMETHEE II method in an Emergency Department. Oper Res Health Care 3(1):1–6

    Article  Google Scholar 

  3. Baykasoğlu A, Gölcük İ (2017) Development of an interval type-2 fuzzy sets based hierarchical MADM model by combining DEMATEL and TOPSIS. Expert Syst Appl 70:37–51

    Article  Google Scholar 

  4. Castillo O, Amador-Angulo L, Castro JR, Garcia-Valdez M (2016) A comparative study of type-1 fuzzy logic systems, interval type-2 fuzzy logic systems and generalized type-2 fuzzy logic systems in control problems. Inf Sci 354:257–274

    Article  Google Scholar 

  5. Castillo O, Cervantes L, Soria J, Sanchez M, Castro JR (2016) A generalized type-2 fuzzy granular approach with applications to aerospace. Inf Sci 354:165–177

    Article  Google Scholar 

  6. Chen CT (2000) Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets Syst 114(1):1–9

    Article  MATH  Google Scholar 

  7. Chen SM, Lee LW (2010) Fuzzy multiple attributes group decision-making based on the ranking values and the arithmetic operations of interval type-2 fuzzy sets. Expert Syst Appl 37(1):824–833

    Article  Google Scholar 

  8. Chen TY (2014) A PROMETHEE-based outranking method for multiple criteria decision analysis with interval type-2 fuzzy sets. Soft Comput 18(5):923–940

    Article  MATH  Google Scholar 

  9. Chen TY (2014) An ELECTRE-based outranking method for multiple criteria group decision making using interval type-2 fuzzy sets. Inf Sci 263:1–21

    Article  MathSciNet  MATH  Google Scholar 

  10. Chen TY, Chang CH, Lu JFR (2013) The extended QUALIFLEX method for multiple criteria decision analysis based on interval type-2 fuzzy sets and applications to medical decision making. Eur J Oper Res 226(3):615–625

    Article  MathSciNet  MATH  Google Scholar 

  11. Chiao KP (2014) Interval type-2 fuzzy sets extension of analytic hierarchy process with application to new product development project screening. In: IEEE 2014 international conference on fuzzy theory and its applications (iFUZZY2014), pp 111–116

  12. Dymova L, Sevastjanov P, Tikhonenko A (2015) An interval type-2 fuzzy extension of the TOPSIS method using alpha cuts. Knowl Based Syst 83:116–127

    Article  Google Scholar 

  13. Dymova L, Sevastjanov P, Tikhonenko A (2016) The TOPSIS method in the interval type-2 fuzzy setting. In :Parallel processing and applied mathematics. Springer, pp 445–454

  14. Gonzalez CI, Melin P, Castro JR, Mendoza O, Castillo O (2017) General type-2 fuzzy edge detection in the preprocessing of a face recognition system. In: Nature-inspired design of hybrid intelligent systems. Springer, pp 3–18

  15. Gonzalez CI, Melin P, Castro JR, Mendoza O, Castillo O (2016) An improved sobel edge detection method based on generalized type-2 fuzzy logic. Soft Comput 20(2):773–784

    Article  Google Scholar 

  16. Görener A, Ayvaz B, Kuşakcı AO, Altınok E (2017) A hybrid type-2 fuzzy based supplier performance evaluation methodology: the Turkish Airlines technic case. Appl Soft Comput 56:436–445

    Article  Google Scholar 

  17. Hashemi H, Bazargan J, Mousavi SM (2013) A compromise ratio method with an application to water resources management: an intuitionistic fuzzy set. Water Resour Manag 27:2029–2051

    Article  Google Scholar 

  18. Hu J, Zhang Y, Chen X, Liu Y (2013) Multi-criteria decision making method based on possibility degree of interval type-2 fuzzy number. Knowl Based Syst 43:21–29

    Article  Google Scholar 

  19. Keshavarz Ghorabaee M, Amiri M, Kazimieras Zavadskas E, Antuchevičienė J (2017) Assessment of third-party logistics providers using a CRITIC–WASPAS approach with interval type-2 fuzzy sets. Transport 32(1):66–78

    Article  Google Scholar 

  20. Kiliç M, Kaya İ (2015) Investment project evaluation by a decision making methodology based on type-2 fuzzy sets. Appl Soft Comput 27:399–410

    Article  Google Scholar 

  21. Lee HS (2005) On fuzzy preference relation in group decision making. Int J Comput Math 82:133–140

    Article  MathSciNet  MATH  Google Scholar 

  22. Madera Q, Castillo O, Garcia M, Mancilla A (2017) Bidding strategies based on type-1 and interval type-2 fuzzy systems for Google AdWords advertising campaigns. In: Nature-inspired design of hybrid intelligent systems. Springer, pp 99–113

  23. Mendel JM (2003) Type-2 fuzzy sets: some questions and answers. IEEE Connect Newsl IEEE Neural Netw Soc 1:10–13

    Google Scholar 

  24. Mendel JM (2007) Type-2 fuzzy sets and systems: an overview. IEEE Comput Intell Mag 2(1):20–29

    Article  Google Scholar 

  25. Mendel JM, John R, Liu F (2006) Interval type-2 fuzzy logic systems made simple. IEEE Trans Fuzzy Syst 14(6):808–821

    Article  Google Scholar 

  26. Mohagheghi V, Mousavi SM, Siadat A (2016) Assessing E-waste recycling programs by developing preference selection index under interval type-2 fuzzy uncertainty. In: 2016 IEEE international conference on industrial engineering and engineering management (IEEM), pp 1259–1263

  27. Mohagheghi V, Mousavi SM, Vahdani B (2016) A new multi-objective optimization approach for sustainable project portfolio selection: a real world application under interval-valued fuzzy environment. Iran J Fuzzy Syst 13(6):41–68

    MathSciNet  Google Scholar 

  28. Mohagheghi V, Mousavi SM, Vahdani B, Siadat A (2017) A mathematical modeling approach for high and new technology-project portfolio selection under uncertain environments. J Intell Fuzzy Syst 32(6):4069–4079

    Article  MATH  Google Scholar 

  29. Mousavi SM, Mirdamadi S, Siadat A, Dantan J, Tavakkoli-Moghaddam R (2015) An intuitionistic fuzzy grey model for selection problems with an application to the inspection planning in manufacturing firms. Eng Appl Artif Intell 39:157–167

    Article  Google Scholar 

  30. Mousavi SM, Vahdani B, Tavakkoli-Moghaddam R, Tajik N (2014) Soft computing based on a fuzzy grey compromise solution approach with an application to the selection problem of material handling equipment. Int J Comput Integr Manuf 27(6):547–569

    Article  Google Scholar 

  31. Otheman A, Abdullah L (2014) A new concept of similarity measure for IT2FS TOPSIS and its use in decision making. In: Proceedings of the 3rd international conference on mathematical sciences, vol 1602, no 1. AIP Publishing, pp 608–614

  32. Qin J, Liu X, Pedrycz W (2015) An extended VIKOR method based on prospect theory for multiple attribute decision making under interval type-2 fuzzy environment. Knowl Based Syst 86:116–130

    Article  Google Scholar 

  33. Qin J, Liu X, Pedrycz W (2017) A multiple attribute interval type-2 fuzzy group decision making and its application to supplier selection with extended LINMAP method. Soft Comput 21(12):3207–3226

    Article  MATH  Google Scholar 

  34. Qin J, Liu X, Pedrycz W (2017) An extended TODIM multi-criteria group decision making method for green supplier selection in interval type-2 fuzzy environment. Eur J Oper Res 258(2):626–638

    Article  MathSciNet  MATH  Google Scholar 

  35. Soner O, Celik E, Akyuz E (2017) Application of AHP and VIKOR methods under interval type 2 fuzzy environment in maritime transportation. Ocean Eng 129:107–116

    Article  Google Scholar 

  36. Tai K, El-Sayed AR, Biglarbegian M, Gonzalez CI, Castillo O, Mahmud S (2016) Review of recent type-2 fuzzy controller applications. Algorithms 9(2):39

    Article  MathSciNet  MATH  Google Scholar 

  37. Vahdani B, Mousavi SM, Ebrahimnejad S (2014) Soft computing-based preference selection index method for human resource management. J Intell Fuzzy Syst 26(1):393–403

    Article  MathSciNet  MATH  Google Scholar 

  38. Wang YJ (2014) A fuzzy multi-criteria decision-making model by associating technique for order preference by similarity to ideal solution with relative preference relation. Inf Sci 268:169–184

    Article  MathSciNet  MATH  Google Scholar 

  39. Wibowo S, Deng H (2015) Multi-criteria group decision making for evaluating the performance of e-waste recycling programs under uncertainty. Waste Manag 40:127–135

    Article  Google Scholar 

  40. Yang C, Chen W, Peng DH (2015) An approach based on TOPSIS for interval type-2 fuzzy multiple attributes decision-making. Int J Control Autom 8(11):81–92

    Article  Google Scholar 

  41. Yeh TM, Pai FY, Liao CW (2014) Using a hybrid MCDM methodology to identify critical factors in new product development. Neural Comput Appl 24(3–4):957–971

    Article  Google Scholar 

  42. Yue Z (2011) A method for group decision-making based on determining weights of decision makers using TOPSIS. Appl Math Model 35(4):1926–1936

    Article  MathSciNet  MATH  Google Scholar 

  43. Yue Z (2013) An avoiding information loss approach to group decision making. Appl Math Model 37(1):112–126

    Article  MathSciNet  MATH  Google Scholar 

  44. Zadeh LA (1975) The concept of a linguistic variable and its application to approximate reasoning—II. Inf Sci 8(4):301–357

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgements

The authors would like to thank the anonymous referees for their valuable comments and feedbacks which improved the primary version of the paper.

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Correspondence to S. Meysam Mousavi.

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Mohagheghi, V., Mousavi, S.M. An analysis approach to handle uncertain multi-criteria group decision problems in the framework of interval type-2 fuzzy sets theory. Neural Comput & Applic 31, 3543–3557 (2019). https://doi.org/10.1007/s00521-017-3275-2

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  • DOI: https://doi.org/10.1007/s00521-017-3275-2

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