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An outranking approach for multi-criteria decision-making problems with interval-valued neutrosophic sets

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Abstract

In this paper, a novel outranking approach for multi-criteria decision-making (MCDM) problems is proposed to address situations where there is a set of numbers in the real unit interval and not just a specific number with a neutrosophic set. Firstly, the operations of interval neutrosophic sets and their related properties are introduced. Then some outranking relations for interval neutrosophic numbers (INNs) are defined based on ELECTRE IV, and the properties of the outranking relations are further discussed in detail. Additionally, based on the outranking relations of INNs, a ranking approach is developed in order to solve MCDM problems. Finally, two practical examples are provided to illustrate the practicality and effectiveness of the proposed approach. Moreover, a comparison analysis based on the same examples is also conducted.

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References

  1. Zadeh LA (1965) Fuzzy sets. Inf Control 8:338–356

    Article  MathSciNet  MATH  Google Scholar 

  2. Zadeh LA (1968) Probability measures of fuzzy events. J Math Anal Appl 23:421–427

    Article  MathSciNet  MATH  Google Scholar 

  3. Turksen IB (1986) Interval valued fuzzy sets based on normal forms. Fuzzy Sets Syst 20:191–210

    Article  MathSciNet  MATH  Google Scholar 

  4. Atanassov KT (1986) Intuitionistic fuzzy sets. Fuzzy Sets Syst 20:87–96

    Article  MathSciNet  MATH  Google Scholar 

  5. Atanassov KT (2000) Two theorems for intuitionistic fuzzy sets. Fuzzy Sets Syst 110:267–269

    Article  MathSciNet  MATH  Google Scholar 

  6. Gau WL, Buehrer DJ (1993) Vague sets. IEEE Trans Syst Man Cybern 23:610–614

    Article  MATH  Google Scholar 

  7. Bustince H, Burillo P (1996) Vague sets are intuitionistic fuzzy sets. Fuzzy Sets Syst 79:403–405

    Article  MathSciNet  MATH  Google Scholar 

  8. Liu HW, Wang GJ (2007) Multi-criteria methods based on intuitionistic fuzzy sets. Eur J Oper Res 179:220–233

    Article  MATH  Google Scholar 

  9. Zhi P, Li Z (2012) A novel approach to multi-attribute decision making based on intuitionistic fuzzy sets. Expert Syst Appl 39:2560–2566

    Article  Google Scholar 

  10. Zeng SZ, Su WH (2011) Intuitionistic fuzzy ordered weighted distance operator. Knowl Based Syst 24(8):1224–1232

    Article  Google Scholar 

  11. Shinoj TK, Sunil JJ (2012) Intuitionistic fuzzy multisets and its application in medical diagnosis. Int J Math Comput Sci 6:34–37

    Google Scholar 

  12. Sotirov S, Sotirova E, Orozova D (2009) Neural network for defining intuitionistic fuzzy sets in e-learning. NIFS 15:33–36

    Google Scholar 

  13. Guo Y, Sengur A (2014) NECM: neutrosophic evidential c-means clustering algorithm. Neural Comput Appl. doi:10.1007/s00521-014-1648-3

    Google Scholar 

  14. Chaira T (2011) A novel intuitionistic fuzzy C means clustering algorithm and its application to medical images. Appl Soft Comput 11:1711–1717

    Article  Google Scholar 

  15. Joshi BP, Kumar S (2012) Fuzzy time series model based on intuitionistic fuzzy sets for empirical research in stock market. Int J Appl Evol Comput 3:71–84

    Article  Google Scholar 

  16. Atanassov KT, Gargov G (1989) Interval valued intuitionistic fuzzy sets. Fuzzy Sets Syst 31:343–349

    Article  MathSciNet  MATH  Google Scholar 

  17. Wang J-Q, Nie R, Zhang H-Y, Chen X-H (2013) New operators on triangular intuitionistic fuzzy numbers and their applications in system fault analysis. Inf Sci 251:79–95

    Article  MathSciNet  MATH  Google Scholar 

  18. Torra V (2010) Hesitant fuzzy sets. Int J Intell Syst 25:529–539

    MATH  Google Scholar 

  19. Torra V, Narukawa Y (2009). On hesitant fuzzy sets and decision. In: Proceedings of the 18th IEEE international conference on fuzzy systems, Jeju Island, Korea, pp 1378–1382

  20. Wang J-Q, Wu J-T, Wang J, Zhang H-Y, Chen X-H (2014) Interval-valued hesitant fuzzy linguistic sets and their applications in multi-criteria decision-making problems. Inf Sci 288:55–72

    Article  MathSciNet  Google Scholar 

  21. Wang J, Zhou P, Li K, Zhang H, Chen X (2014) Multi-criteria decision-making method based on normal intuitionistic fuzzy-induced generalized aggregation operator. TOP 22:1103–1122

    Article  MathSciNet  Google Scholar 

  22. Wang J, Wu J, Wnag J, Zhang H, Chen X (2015) Multi-criteria decision-making methods based on the Hausdorff distance of hesitant fuzzy linguistic numbers. Soft Comput. doi:10.1007/s00500-015-1609-5

    Google Scholar 

  23. Wang J-Q, Peng J-J, Zhang H-Y, Liu T, Chen X-H (2015) An uncertain linguistic multi-criteria group decision-making method based on a cloud model. Group Decis Negot 24(1):171–192

    Article  Google Scholar 

  24. Wei G (2010) Some induced geometric aggregation operators with intuitionistic fuzzy information and their application to group decision making. Appl Soft Comput 10(2):423–431

    Article  Google Scholar 

  25. Wang H, Smarandache F, Zhang YQ, Sunderraman R (2010) Single valued neutrosophic sets. Multisp Multistruct 4:410–413

    MATH  Google Scholar 

  26. Smarandache F (1999) A unifying field in logics. Neutrosophy: neutrosophic probability, set and logic. American Research Press, Rehoboth

    MATH  Google Scholar 

  27. Smarandache F (2003) A unifying field in logics neutrosophic logic. Neutrosophy, neutrosophic set, neutrosophic probability. American Research Press, Rehoboth

    MATH  Google Scholar 

  28. Rivieccio U (2008) Neutrosophic logics: prospects and problems. Fuzzy Sets Syst 159(14):1860–1868

    Article  MathSciNet  MATH  Google Scholar 

  29. Majumdarar P, Samant SK (2014) On similarity and entropy of neutrosophic sets. J Intell Fuzzy Syst 26:1245–1252

    MathSciNet  Google Scholar 

  30. Ye J (2014) Single valued neutrosophic cross-entropy for multicriteria decision making problems. Appl Math Model 38(3):1170–1175

    Article  MathSciNet  Google Scholar 

  31. Ye J (2014) A multicriteria decision-making method using aggregation operators for simplified neutrosophic sets. J Intell Fuzzy Syst 26:2459–2466

    MathSciNet  MATH  Google Scholar 

  32. Liu P, Wang Y (2014) Multiple attribute decision-making method based on single-valued neutrosophic normalized weighted Bonferroni mean. Neural Comput Appl. doi:10.1007/s00521-014-1688-8

    Google Scholar 

  33. Peng J-J, Wang J-Q, Wang J, Zhang H-Y, Chen X-H (2015) Simplified neutrosophic sets and their applications in multi-criteria group decision-making problems. Int J Syst Sci. doi:10.1080/00207721.2014.994050

    Google Scholar 

  34. Wang H, Smarandache F, Zhang Y-Q, Sunderraman R (2005) Interval neutrosophic sets and logic: theory and applications in computing. Hexis, Arizona

    MATH  Google Scholar 

  35. Lupiáñez FG (2009) Interval neutrosophic sets and topology. Kybernetes 38(3/4):621–624

    Article  MATH  Google Scholar 

  36. Broumi S, Smarandache F (2015) New Operations on Interval Neutrosophic Sets. Journal of New Theory 1:24–37

    Google Scholar 

  37. Broumi S, Smarandache F (2013) Correlation coefficient of interval neutrosophic set. Appl Mech Mater 436:511–517

    Article  Google Scholar 

  38. Broumi S, Smarandache F (2014) Cosine similarity measure of interval valued neutrosophic sets. Neutrosophic Sets Syst 5:15–20

    Google Scholar 

  39. Zhang HY, Wang JQ, Chen XH (2014) Interval neutrosophic sets and their application in multicriteria decision making problems. Sci World J 2014:645953

    Google Scholar 

  40. Liu P, Shi L (2014) The generalized hybrid weighted average operator based on interval neutrosophic hesitant set and its application to multiple attribute decision making. Neural Comput Appl. doi:10.1007/s00521-014-1736-4

    Google Scholar 

  41. Broumi S, Smarandache F (2014) Single valued neutrosophic trapezoid linguistic aggregation operators based multi-attribute decision making. Bull Pure Appl Sci Math Stat 33e(2):135–155

    Article  Google Scholar 

  42. Broumi S, Ye J, Smarandache F (2014) An extended TOPSIS method for multiple attribute decision making based on interval neutrosophic uncertain linguistic variables. Neutrosophic Sets Syst 7:1–11

    Google Scholar 

  43. Tian Z-P, Wang J, Zhang H-Y, Chen X-H, Wang J-Q (2015) Simplified neutrosophic linguistic normalized weighted Bonferroni mean operator and its application to multi-criteria decision-making problems. Filomat. doi:10.2298/FIL1508576F

    Google Scholar 

  44. Wang JQ, Li XE (2015) An application of the TODIM method with multi-valued neutrosophic set. Control Decis. doi:10.13195/j.kzyjc.2014.0467

    Google Scholar 

  45. Peng J-J, Wang J-Q, Wu X-H, Wang J, Chen X-H (2015) Multi-valued neutrosophic sets and power aggregation operators with their applications in multi-criteria group decision-making problems. Int J Comput Intell Syst 8(2):345–363

    Article  Google Scholar 

  46. Cağman N, Deli İ (2012) Products of FP-soft sets and their applications. Hacet J Math Stat 41(3):365–374

    MathSciNet  MATH  Google Scholar 

  47. Cağman N, Deli İ (2012) Means of FP-soft sets and their applications. Hacet J Math Stat 41(5):615–625

    MathSciNet  MATH  Google Scholar 

  48. Deli İ, Cağman N (2015) Intuitionistic fuzzy parameterized soft set theory and its decision making. Appl Soft Comput 28:109–113

    Article  Google Scholar 

  49. Deli İ, Broumi S (2015) Neutrosophic soft matrices and NSM-decision making. J Intell Fuzzy Syst. doi:10.3233/IFS-141505

    MathSciNet  MATH  Google Scholar 

  50. Deli İ, Broumi S (2015) Neutrosophic soft relations and some properties. Ann Fuzzy Math Inf 9(1):169–182

    MathSciNet  MATH  Google Scholar 

  51. Broumi S (2013) Generalized neutrosophic soft set. Int J Comput Sci Eng Inf Technol 3(2):17–30

    Google Scholar 

  52. Broumi S, Deli İ, Smarandache F (2014) Relations on interval valued neutrosophic soft sets. J New Results Sci 5:1–10

    MATH  Google Scholar 

  53. Broumi S, Şahin R, Smarandache F (2014) Generalized interval neutrosophic soft set and its decision making problem. J New Results Sci 7:9–47

    Google Scholar 

  54. Broumi S, Smarandache F (2014) Lower and upper soft interval valued neutrosophic rough approximations of an IVNSS-relation. SISOM Acoust 1:204–211

    Google Scholar 

  55. Broumi S, Smarandache F (2015) Interval-valued neutrosophic soft rough sets. Int J Comput Math 2015:1–13

    Article  MathSciNet  Google Scholar 

  56. Roy B (1991) The outranking approach and the foundations of ELECTRE methods. Theor Decis 31:49–73

    Article  MathSciNet  Google Scholar 

  57. Peng J-J, Wang J-Q, Zhang H-Y, Chen X-H (2014) An outranking approach for multi-criteria decision-making problems with simplified neutrosophic sets. Appl Soft Comput 25:336–346

    Article  Google Scholar 

  58. Orner JL, Kirkwood CW (1991) Decision analysis applications in the operations research literature 1970–1989. Oper Res 39:206–219

    Article  Google Scholar 

  59. Haurant P, Oberti P, Muselli M (2011) Multicriteria selection aiding related to photovoltaic plants on farming fields on Corsica island: a real case study using the ELECTRE outranking framework. Energy Policy 39(2):676–688

    Article  Google Scholar 

  60. Figueira JR, Almeida-Dias J, Matias S, Roy B, Carvalho MJ, Plancha CE (2011) Electre Tri-C, a multiple criteria decision aiding sorting model applied to assisted reproduction. Int J Med Inf 80(4):262–273

    Article  Google Scholar 

  61. Pasiouras F, Tanna S, Zopounidis C (2007) The identification of acquisition targets in the EU banking industry: an application of multicriteria approaches. Int Rev Financ Anal 16(3):262–281

    Article  Google Scholar 

  62. Cavallaro F (2010) A comparative assessment of thin-film photovoltaic production processes using the ELECTRE III method. Energy Policy 38(1):463–474

    Article  Google Scholar 

  63. Montazer GA, Saremi HQ, Ramezani M (2009) Design a new mixed expert decision aiding system using fuzzy ELECTRE III method for vendor selection. Expert Syst Appl 36(8):10837–10847

    Article  Google Scholar 

  64. Abedi M, Torabi SA, Norouzi G-H, Hamzeh M (2012) ELECTRE III: a knowledge-driven method for integration of geophysical data with geological and geochemical data in mineral prospectivity mapping. J Appl Geophys 87:9–18

    Article  Google Scholar 

  65. Roy B (1977) Partial preference analysis and decision-aid: the fuzzy outranking relation concept. In: Bell DE, Keeney RL, Raiffa H (eds) Conflicting objectives and decisions. Wiley, New York, pp 40–75

    Google Scholar 

  66. Figueira JR, Greco S, Ehrgott M (2005) Multiple criteria decision analysis: state of the art surveys. Kluwer, Boston

    Book  MATH  Google Scholar 

  67. Almeida-Dias J, Figueira JR, Roy B (2010) ELECTRE TRI-C: a multiple criteria sorting method based on characteristic reference actions. Eur J Oper Res 204(3):565–580

    Article  MathSciNet  MATH  Google Scholar 

  68. Chen T-Y (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 

  69. Xu J, Shen F (2014) A new outranking choice method for group decision making under Atanassov’s interval-valued intuitionistic fuzzy environment. Knowl Based Syst 70:177–188

    Article  Google Scholar 

  70. Wang JQ, Wang DD, Zhang HY, Chen XH (2013) Multi-criteria outranking approach with hesitant fuzzy sets. OR Spectr 36(4):1001–1019

    Article  MathSciNet  MATH  Google Scholar 

  71. Peng J, Wnag J, Wang J, Yang L, Chen X (2015) An extension of ELECTRE to Multi-criteria decision-making problems with multi-hesitant fuzzy sets. Inf Sci 307:113–126

    Article  MathSciNet  Google Scholar 

  72. Wang J-Q, Wang J, Chen Q-H, Zhang H-Y, Chen X-H (2014) An outranking approach for multi-criteria decision-making with hesitant fuzzy linguistic term sets. Inf Sci 280:338–351

    Article  MathSciNet  Google Scholar 

  73. Yang W-E, Wang J-Q (2013) Multi-criteria semantic dominance: a linguistic decision aiding technique based on incomplete preference information. Eur J Oper Res 231(1):171–181

    Article  MathSciNet  MATH  Google Scholar 

  74. Roy B (1982) Ranking of suburban line extension projects on the Paris metro system by a multicriteria method. Transp Res Part A Gen 16:301–312

    Article  Google Scholar 

  75. Roy B, Vincke P (1984) Relational systems of preference with one or more pseudo-criteria: some new concepts and results. Manag Sci 30(11):1323–1335

    Article  MathSciNet  MATH  Google Scholar 

  76. Figueira JR, Greco S, Roy B, Słowiński R (2010) ELECTRE methods: main features and recent developments. In: Zopounidis C, Pardalos P (eds) Handbook of multicriteria analysis. Springer, Berlin, pp 51–89

    Chapter  Google Scholar 

  77. Tzeng GH, Huang JJ (2011) Multiple attribute decision making: methods and applications. Chapman and Hall, London

    MATH  Google Scholar 

  78. Ye J (2012) Multicriteria decision-making method using the Dice similarity measure based on the reduct intuitionistic fuzzy sets of interval-valued intuitionistic fuzzy sets. Appl Math Model 36(9):4466–4472

    Article  MathSciNet  MATH  Google Scholar 

  79. 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 

  80. Ye J (2014) Similarity measures between interval neutrosophic sets and their applications in multicriteria decision-making. J Intell Fuzzy Syst 26:165–172

    MATH  Google Scholar 

  81. Ye J (2013) Multicriteria decision-making method using the correlation coefficient under single-valued neutrosophic environment. Int J Gen Syst 42(4):386–394

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgments

This work was partly supported by Humanities and Social Sciences Foundation of Ministry of Education of China (No. 11YJCZH227) and the National Natural Science Foundation of China (Nos. 71221061 and 71210003). The authors also would like to express appreciation to the anonymous reviewers and editors for their helpful comments that improved the paper.

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Zhang, H., Wang, J. & Chen, X. An outranking approach for multi-criteria decision-making problems with interval-valued neutrosophic sets. Neural Comput & Applic 27, 615–627 (2016). https://doi.org/10.1007/s00521-015-1882-3

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