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An extended Pythagorean fuzzy VIKOR method with risk preference and a novel generalized distance measure for multicriteria decision-making problems

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Abstract

This study aims to extend classic VIKOR technique for multicriteria decision-making (MCDM) problems within Pythagorean fuzzy (PF) scenario. First, judgments from decision makers (DMs) are expressed by PF sets that can describe more uncertain and ambiguous information than available fuzzy sets. Second, PF point operators are applied to denote the risk preference of the DM who may express an attitude toward an emerging science and technology. Third, a new generalized distance measurement formula considering all the characteristics of PF sets is proposed, and some attractive properties of distance measure, which outperforms available distance measures, are proved. Fourth, the novel generalized distance measure is employed to relative distance to identify the optimum and worst PF values and then employed in \(L_{p}\)-metric VIKOR formula to accurately gain the group utility, individual regret, and compromise index. The novel PF-VIKOR algorithm considering DM’s risk preference and a novel distance measure is described in detail, and a blockchain technology solution selection problem is utilized to validate the feasibility of our technique. Then, the sensitivity analysis is implemented to test stability of our PF-VIKOR technique when the parameters in risk preferences and generalized distance measure are adjusted. Fifth, the comparison among various PF-MCDM techniques is performed to validate superiority and practicability of our presented technique.

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Data availability statement

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

References

  1. Ak MF, Gul M (2019) AHP-TOPSIS integration extended with Pythagorean fuzzy sets for information security risk analysis. Complex Intell Syst 5:113–126. https://doi.org/10.1007/s40747-018-0087-7

    Article  Google Scholar 

  2. Akram M, Ilyas F, Garg H (2019) Multi-criteria group decision making based on ELECTRE I method in Pythagorean fuzzy information. Soft Comput 24:3425–3453. https://doi.org/10.1007/s00500-019-04105-0

    Article  Google Scholar 

  3. Akram M, Luqman A, Alcantud JCR (2020) Risk evaluation in failure modes and effects analysis: hybrid TOPSIS and ELECTRE I solutions with Pythagorean fuzzy information. Neural Comput Appl. https://doi.org/10.1007/s00521-020-05350-3

    Article  Google Scholar 

  4. Atanassov KT (1986) Intuitionistic fuzzy sets. Fuzzy Sets Syst 20(1):87–96. https://doi.org/10.1016/S0165-0114(86)80034-3

    Article  MATH  Google Scholar 

  5. Atanassov KT (1995) Remarks on the intuitionistic fuzzy sets-III. Fuzzy Sets Syst 75(3):401–402. https://doi.org/10.1016/0165-0114(95)00004-5

    Article  MathSciNet  MATH  Google Scholar 

  6. Atanassov KT (2016) Review and new results on intuitionistic fuzzy sets. Int J Bioautom 20(1):7–16

    Google Scholar 

  7. Balin A, Sener B, Demirel H (2019) Application of fuzzy VIKOR method for the evaluation and selection of a suitable tugboat. J Eng Marit Environ https://doi.org/10.1177/475090219875879

    Article  Google Scholar 

  8. Biswas A, Sarkar B (2018) Interval-valued Pythagorean fuzzy TODIM approach through point operator-based similarity measures for multicriteria group decision making. Kybernetes 48(3):496–519. https://doi.org/10.1108/K-12-2017-0490

    Article  Google Scholar 

  9. Chen TY (2018) Remoteness index-based Pythagorean fuzzy VIKOR methods with a generalized distance measure for multiple criteria decision analysis. Inf Fusion 41:129–150. https://doi.org/10.1016/j.inffus.2017.09.003

    Article  Google Scholar 

  10. Chen TY (2019) A novel VIKOR method with an application to multiple criteria decision analysis for hospital-based post-acute care within a highly complex uncertain environment. Neural Comput Appl 31(8):3969–3999. https://doi.org/10.1007/s00521-017-3326-8

    Article  Google Scholar 

  11. Chen TY (2019) A novel PROMETHEE-based method using a Pythagorean fuzzy combinative distance-based precedence approach to multiple criteria decision making. Appl Soft Comput 82:105560. https://doi.org/10.1016/j.asoc.2019.105560

    Article  Google Scholar 

  12. Chen TY (2020) New Chebyshev distance measures for Pythagorean fuzzy sets with applications to multiple criteria decision analysis using an extended ELECTRE approach. Expert Syst Appl 147:113164. https://doi.org/10.1016/j.eswa.2019.113164

    Article  Google Scholar 

  13. Chen TY (2021) Pythagorean fuzzy linear programming technique for multidimensional analysis of preference using a squared-distance-based approach for multiple criteria decision analysis. Expert Syst Appl 164:113908. https://doi.org/10.1016/j.eswa.2020.113908

    Article  Google Scholar 

  14. Deli İ (2019) A novel defuzzificationmethod of SV-trapezoidal neutrosophic numbers and multi-attribute decision making: a comparative analysis. Soft Comput 23:12529–12545. https://doi.org/10.1007/s00500-019-03803-z

    Article  Google Scholar 

  15. Deli İ (2019) Some operators with IVGSVTrN-numbers and their applications to multiple criteria group decision making. Neutrosophic Sets Syst 25:33–53

    Google Scholar 

  16. Deli İ (2020) A TOPSIS method by using generalized trapezoidal hesitant fuzzy numbers and application to a robot selection problem. J Intell Fuzzy Syst 38(1):779–793. https://doi.org/10.3233/JIFS-179448

    Article  Google Scholar 

  17. Deli İ (2020) Linear optimization method on single valued neutrosophic set and its sensitivity analysis. TWMS J Appl Eng Math 10(1):128–137

    Google Scholar 

  18. Deli I, Çağman N (2016) Similarity measure of IFS-sets and its application in medical diagnosis. Ann Fuzzy Math Inf 11(5):841–854

    MathSciNet  MATH  Google Scholar 

  19. Deli İ, Şubaş Y (2017) Some weighted geometric operators with SVTrN-numbers and their application to multi-criteria decision making problems. J Intell Fuzzy Syst 32(1):291–301. https://doi.org/10.3233/JIFS-151677

    Article  MATH  Google Scholar 

  20. Fei L, Deng Y (2019) Multi-criteria decision making in Pythagorean fuzzy environment. Appl Intell 50:537–561. https://doi.org/10.1007/s10489-019-01532-2

    Article  Google Scholar 

  21. Garg H (2021) A new possibility degree measure for interval-valued q-rung orthopair fuzzy sets in decision-making. Int J Intell Syst 36:526–557. https://doi.org/10.1002/int.22308

    Article  Google Scholar 

  22. Ghadikolaei AS, Madhoushi M, Divsalar M (2018) Extension of the VIKOR method for group decision making with extended hesitant fuzzy linguistic information. Neural Comput Appl 30(12):3589–3602. https://doi.org/10.1007/s00521-017-2944-5

    Article  Google Scholar 

  23. Gomes L, Lima M (1992) TODIM: Basics and application to multicriteria ranking of projects with environmental impacts. Foundations of Computing and Decision Sciences 16(4):113–127

    MATH  Google Scholar 

  24. Gul M, Celik E, Aydin N, Taskin Gumus A, Guneri AF (2016) A state of the art literature review of VIKOR and its fuzzy extensions on applications. Appl Soft Comput 46:60–89. https://doi.org/10.1016/j.asoc.2016.04.040

    Article  Google Scholar 

  25. Gul M, Ak MF, Guneri AF (2019) Pythagorean fuzzy VIKOR-based approach for safety risk assessment in mine industry. J Saf Res 69:135–153. https://doi.org/10.1016/j.jsr.2019.03.005

    Article  Google Scholar 

  26. Gupta V (2017) A brief history of blockchain. Harvard Business Review, Boston

    Google Scholar 

  27. Gupta P, Mehlawat MKN, Grover N (2016) Intuitionistic fuzzy multi-attribute group decision-making with an application to plant location selection based on a new extended VIKOR method. Inf Sci. https://doi.org/10.1016/j.ins.2016.07.058

    Article  Google Scholar 

  28. Han Y, Deng Y, Cao Z, Lin CT (2020) An interval-valued Pythagorean prioritized operator-based game theoretical framework with its applications in multicriteria group decision making. Neural Comput Appl 32:7641–7659. https://doi.org/10.1007/s00521-019-04014-1

    Article  Google Scholar 

  29. Holotiuk F, Pisani F, Moormann F (2019) Radicalness of blockchain: an assessment based on its impact on the payments industry. Technol Anal Strateg Manag 31(8):915–928. https://doi.org/10.1080/09537325.2019.1574341

    Article  Google Scholar 

  30. Ilbahar E, Karaşan A, Cebi S, Kahraman C (2018) A novel approach to risk assessment for occupational health and safety using Pythagorean fuzzy AHP & fuzzy inference system. Saf Sci 103:124–136. https://doi.org/10.1016/j.ssci.2017.10.025

    Article  Google Scholar 

  31. Kahneman D, Tversky A (1979) Prospect theory: an analysis of decision under risk. Econometrica 47(2):263. https://doi.org/10.1017/CBO9780511609220.014

    Article  MathSciNet  MATH  Google Scholar 

  32. Karasan A, Ilbahar E, Kahraman C (2019) A novel pythagorean fuzzy AHP and its application to landfill site selection problem. Soft Comput 23:10953–10968. https://doi.org/10.1007/s00500-018-3649-0

    Article  Google Scholar 

  33. Kaya A, Çiçekalan B, Çebi F (2020) Location selection for WEEE recycling plant by using Pythagorean fuzzy AHP. J Intell Fuzzy Syst 38(1):1097–1106. https://doi.org/10.3233/JIFS-179471

    Article  Google Scholar 

  34. Kha MSA, Abdullah S, Ali A, Amin F (2019) An extension of VIKOR method for multi-attribute decision-making under Pythagorean hesitant fuzzy setting. Granul Comput 4(3):421–434. https://doi.org/10.1007/s41066-018-0102-9

    Article  Google Scholar 

  35. Khan MJ, Ali MI, Kuman P (2020) A new ranking technique for q-rung orthopair fuzzy values. Int J Intell Syst 36(1):558–592. https://doi.org/10.1002/int.22311

    Article  Google Scholar 

  36. Kim JH, Ahn BS (2019) Extended VIKOR method using incomplete criteria weights. Expert Syst Appl 126:124–132. https://doi.org/10.1016/j.eswa.2019.02.019

    Article  Google Scholar 

  37. Li DQ, Zeng WY (2018) Distance measure of Pythagorean fuzzy sets. Int J Intell Syst 33(2):348–361. https://doi.org/10.1002/int.21934

    Article  MathSciNet  Google Scholar 

  38. Liang D, Zhang Y, Xu Z, Jamaldeen A (2019) Pythagorean fuzzy VIKOR approaches based on TODIM for evaluating internet banking website quality of Ghanaian banking industry. Appl Soft Comput 78:583–594. https://doi.org/10.1016/j.asoc.2019.03.006

    Article  Google Scholar 

  39. Liu HC, Wu J, Li P (2013) Assessment of health-care waste disposal methods using a VIKOR-based fuzzy multi-criteria decision making method. Waste Manag 33(12):2744–2751. https://doi.org/10.1016/j.wasman.2013.08.006

    Article  Google Scholar 

  40. Lu JP, He TT, Wei GW, Wu J, Wei C (2020) Cumulative prospect theory: performance evaluation of government purchases of home-based elderly-care services using the Pythagorean 2-tuple linguistic TODIM method. Int J Environ Res Public Health 17(6):1939. https://doi.org/10.3390/ijerph17061939

    Article  Google Scholar 

  41. Ma Z, Xu Z (2016) Symmetric Pythagorean fuzzy weighted geometric/averaging operators and their application in multicriteria decision-making problems. J Intell Syst 31(12):1198–1219. https://doi.org/10.1002/int.21823

    Article  Google Scholar 

  42. Mete S, Serin F, Oz NE, Guk M (2019) A decision-support system based on Pythagorean fuzzy VIKOR for occupational risk assessment of a natural gas pipeline construction. J Natural Gas Sci Eng 71:1–12. https://doi.org/10.1016/j.jngse.2019.102979

    Article  Google Scholar 

  43. Meksavang P, Shi H, Lin SM, Liu HC (2019) An extended picture fuzzy VIKOR approach for sustainable supplier management and its application in the beef industry. Symmetry. https://doi.org/10.3390/sym11040468

    Article  Google Scholar 

  44. Mishra AR, Rani P (2019) Shapley divergence measures with VIKOR method for multi-attribute decision-making problems. Neural Comput Appl 31(2):1299–1316. https://doi.org/10.1007/s00521-017-3101-x

    Article  Google Scholar 

  45. Nakamoto S (2008) Bitcoin: a peer-to-peer electronic cash system. https://bitcoin.org/bitcoin.pdf.

  46. Opricovic S (1998) Multicriteria optimization of civil engineering systems. Faculty of Civil Engineering, Belgrade

    Google Scholar 

  47. Opricovic S, Tzeng GH (2002) Multicriteria planning of post-earthquake sustainable reconstruction. Comput Aided Civ Infrastruct Eng 17(3):211–220. https://doi.org/10.1111/1467-8667.00269

    Article  Google Scholar 

  48. Opricovic S, Tzeng GH (2004) The compromise solution by MCDM methods: a comparative analysis of VIKOR and TOPSIS. Eur J Oper Res 156(2):445–455. https://doi.org/10.1016/S0377-2217(03)00020-1

    Article  MATH  Google Scholar 

  49. Opricovic S, Tzeng GH (2007) Extended VIKOR method in comparison with outranking methods. Eur J Oper Res 178(2):514–529. https://doi.org/10.1016/j.ejor.2006.01.020

    Article  MATH  Google Scholar 

  50. Peng X, Dai J (2017) Approaches to Pythagorean fuzzy stochastic multi-criteria decision making based on prospect theory and regret theory with new distance measure and score function. Int J Intell Syst 32(11):1187–1214. https://doi.org/10.1002/int.21896

    Article  Google Scholar 

  51. Peng X, Yang Y (2015) Some results for Pythagorean fuzzy sets. Int J Intell Syst 30(11):1133–1160. https://doi.org/10.1002/int.21738

    Article  MathSciNet  Google Scholar 

  52. Peng X, Yang Y (2016) Fundamental properties of interval-valued Pythagorean fuzzy aggregation operators. Int J Intell Syst 31(5):444–487. https://doi.org/10.1002/int.21790

    Article  Google Scholar 

  53. Peng X, Yang Y (2016) Pythagorean fuzzy Choquet integral based MABAC method for multiple attribute group decision making. Int J Intell Syst 31(10):989–1020. https://doi.org/10.1002/int.21814

    Article  Google Scholar 

  54. Rani P, Mishra AR, Pardasani KR, Mardani A, Liao H, Streimikiene D (2019) A novel VIKOR approach based on entropy and divergency measures of Pythagorean fuzzy sets to evaluate renewable technologies in India. J Clean Prod 238(20):1–17. https://doi.org/10.1016/j.jclepro.2019.117936

    Article  Google Scholar 

  55. Rani P, Mishra AR, Rezaei G, Liao H (2020) Extended Pythagorean fuzzy TOPSIS method based on similarity measure for sustainable recycling partner selection. Int J Fuzzy Syst 22:735–747. https://doi.org/10.1007/s40815-019-00689-9

    Article  Google Scholar 

  56. Ren P, Xu Z, Gou X (2016) Pythagorean fuzzy TODIM approach to multi-criteria decision making. Appl Soft Comput 42:246–259. https://doi.org/10.1016/j.asoc.2015.12.020

    Article  Google Scholar 

  57. Senapati T, Yager RR (2019) Fermatean fuzzy sets. J Ambient Intell Human Comput 11(2):663–674. https://doi.org/10.1007/s12652-019-01377-0

    Article  Google Scholar 

  58. Senapati T, Yager RR (2019) Some new operations over Fermatean fuzzy numbers and application of Fermatean fuzzy WPM in multiple criteria decision making. Informatica 30(2):391–412. https://doi.org/10.15388/Informatica.2019.211

    Article  Google Scholar 

  59. Soner O, Xu Z, Gou X (2017) Application of AHP and VIKOR methods under interval type 2 fuzzy environment in maritime transportation. Ocean Eng 129:107–116. https://doi.org/10.1016/j.oceaneng.2016.11.010

    Article  Google Scholar 

  60. Sun C, Li SY, Deng Y (2020) Determining weights in multi-criteria decision making based on negation of probability distribution under uncertain environment. Mathematics 8(2):191. https://doi.org/10.3390/math8020191

    Article  MathSciNet  Google Scholar 

  61. Varma JR (2019) Blockchain in finance. J Decis Mak 44(1):1–11. https://doi.org/10.1177/0256090919839897

    Article  Google Scholar 

  62. Wan SP, Wang QY, Dong JY (2013) The extended VIKOR method for multi-attribute group decision making with triangular intuitionistic fuzzy numbers. Knowl Based Syst 52:65–77. https://doi.org/10.1016/j.knosys.2013.06.019

    Article  Google Scholar 

  63. Wan SP, Jin Z, Dong JY (2018) Pythagorean fuzzy mathematical programming method for multiattribute group decision making with Pythagorean fuzzy truth degrees. Knowl Inf Syst 55(2):437–466. https://doi.org/10.1007/s10115-017-1085-6

    Article  Google Scholar 

  64. Wan SP, Jin Z, Dong JY (2020) A new order relation for Pythagorean fuzzy numbers and application to multi-attribute group decision making. Knowl Inf Syst 62(2):751–785. https://doi.org/10.1007/s10115-019-01369-8

    Article  Google Scholar 

  65. Wang R, Lin Z, Luo H (2018) Blockchain, bank credit and SME financing. Qual Quant 53(3):1127–1140. https://doi.org/10.1007/s11135-018-0806-6

    Article  Google Scholar 

  66. Yager RR (2013) Pythagorean fuzzy subsets. In: Proceedings of the 2013 joint IFSA world congress and NAFIPS annual meeting, Edmonton, Canada, pp 57–61

  67. Yager RR (2014) Pythagorean membership grades in multicriteria decision making. IEEE Trans Fuzzy Syst 22(4):958–965. https://doi.org/10.1109/TFUZZ.2013.2278989

    Article  Google Scholar 

  68. Yang W, Pang Y (2018) Hesitant interval-valued Pythagorean fuzzy VIKOR method. Int J Intell Syst 34(5):754–789. https://doi.org/10.1002/int.22075

    Article  Google Scholar 

  69. Zadeh LA (1965) Fuzzy sets. Inf Control 8(3):338–353. https://doi.org/10.1016/S0019-9958(65)90241-X

    Article  MATH  Google Scholar 

  70. Zeng SZ, Chen SM, Kuo LW (2019) Multiattribute decision making based on novel score function of intuitionistic fuzzy values and modified VIKOR method. Inf Sci 488:76–92. https://doi.org/10.1016/j.ins.2019.03.018

    Article  Google Scholar 

  71. Zeng WY, Li DQ, Yin Q (2018) Distance and similarity measures of Pythagorean fuzzy sets and their applications to multiple criteria group decision making. Int J Intell Syst 33(11):2236–2254. https://doi.org/10.1002/int.22027

    Article  Google Scholar 

  72. Zhan J, Sun B, Zhang X (2020) PF-TOPSIS method based on CPFRS models: an application to unconventional emergency events. Comput Ind Eng 139:106192. https://doi.org/10.1016/j.cie.2019.106192

    Article  Google Scholar 

  73. Zhang X (2016) Multicriteria Pythagorean fuzzy decision analysis: a hierarchical QUALIFLEX approach with the closeness index-based ranking methods. Inf Sci 330(10):104–124. https://doi.org/10.1016/j.ins.2015.10.012

    Article  Google Scholar 

  74. Zhang X (2017) Pythagorean fuzzy clustering analysis: a hierarchical clustering algorithm with the ratio index-based ranking methods. Int J Intell Syst 33(9):1798–1822. https://doi.org/10.1002/int.21915

    Article  Google Scholar 

  75. Zhang X, Xu Z (2014) Extension of TOPSIS to multiple criteria decision making with Pythagorean fuzzy sets. Int J Intell Syst 29(12):1061–1078. https://doi.org/10.1002/int.21676

    Article  Google Scholar 

  76. Zhou F, Chen TY (2020) Multiple criteria group decision analysis using a Pythagorean fuzzy programming model for multidimensional analysis of preference based on novel distance measures. Comput Ind Eng 148:106670. https://doi.org/10.1016/j.cie.2020.106670

    Article  Google Scholar 

  77. Zhou F, Chen TY (2020) An integrated multicriteria group decision-making approach for green supplier selection under Pythagorean fuzzy scenarios. IEEE Access 8:165216–165231. https://doi.org/10.1109/ACCESS.2020.3022377

    Article  Google Scholar 

  78. Zhu L, Liang X, Wang L, Wu X (2018) Generalized pythagorean fuzzy point operators and their application in multi-attributes decision making. J Intell Fuzzy Syst 35(2):1407–1418. https://doi.org/10.3233/jifs-169683

    Article  Google Scholar 

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Acknowledgments

The authors acknowledge the assistance of the respected editor and the anonymous referees for their insightful and constructive comments, which helped to improve the overall quality of the paper. The corresponding author is grateful for grant funding support from the Ministry of Science and Technology, Taiwan (MOST 108-2410-H-182-014-MY2), and Chang Gung Memorial Hospital, Linkou, Taiwan (BMRP 574), during the completion of this study.

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FZ contributed to conceptualization, methodology, software, validation, formal analysis, data curation, writing—original draft, visualization, and writing—review and editing. T-YC was involved in conceptualization, methodology, validation, writing—original draft, writing—review and editing, supervision, and funding acquisition.

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Correspondence to Ting-Yu Chen.

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Zhou, F., Chen, TY. An extended Pythagorean fuzzy VIKOR method with risk preference and a novel generalized distance measure for multicriteria decision-making problems. Neural Comput & Applic 33, 11821–11844 (2021). https://doi.org/10.1007/s00521-021-05829-7

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