Research Article
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Year 2025, Volume: 17 Issue: 1, 243 - 263, 30.06.2025
https://doi.org/10.47000/tjmcs.1677588

Abstract

References

  • Alvaredo, F., Chancel, L., Piketty, T., Saez, E., Zucman, G., Global Inequality Dynamics: New Findings from WID.world, American Economic Review, 107(5)(2017), 404–409.
  • Ashraf, S., Abdullah, S., Mahmood, T., Ghani, F., Mahmood, T., Spherical fuzzy sets and their applications in multi-attribute decision-making problems, J. Intell. Fuzzy Syst., 36(3)(2019), 2829–2844.
  • Ashraf Ganjoei, R., Akbarifard, H., Mashinchi, M., Jalaee Esfandabadi, S.A., Applying of fuzzy Nonlinear Regression to Investigate the Effect of Information and Communication Technology (ICT) on Income Distribution, vol.2021(2021), 1–11.
  • Atanassov, K.T., Intuitionistic fuzzy sets, In Intuitionistic fuzzy sets, Physica, Heidelberg, 1999.
  • Atanassov, K., Gargov, G., Interval-valued fuzzy set, Fuzzy Sets and Systems, 31, 343–349 (1989).
  • Aydoğan, B., Ünver, M., A modified similarity measure for continuous function valued intuitionistic fuzzy sets and an application on classification, Springer Proceeding in Mathematics and Statistics (accepted).
  • Atkinson, A.B., Income inequality in OECD countries: Data and Explanations, CESifo Economic Studies, 49(4)(2003), 479–513.
  • Bai, Z., An interval-vValued iIntuitionistic fuzzy TOPSIS method based on an improved score function, The Scientific World Journal, 2013(2013), 1–6.
  • Bedregal, B., Lima, L., Rocha, M., Dimuro, G., Bustince, H., Interval-valued Atanassov intuitionistic t-norms and t-conorms endowed with the usual or admissible orders, Comput. Appl. Math., 42(1)(2023), 49.
  • Beliakov, G., Bustince, H., Goswami, D.P., Mukherjee, U.K., Pal, N.R., On averaging operators for Atanassov’s intuitionistic fuzzy sets, Information Sciences, 181(6)(2011), 1116–1124.
  • Bozyiğit, M.C., Olgun, M., Ünver, M., Söylemez, D., Parametric picture fuzzy cross-entropy measures based on d-Choquet integral for building material recognition, Applied Soft Computing, 166(2024), 112167.
  • Bozyigit, M.C., Smarandache, F., Olgun, M., Ünver, M., A new type of neutrosophic set in Pythagorean fuzzy environment and applications to multi-criteria decision-making, International Journal of Neutrosophic Science, 20(2)(2023), 107–134.
  • Burtless, G., Effects of growing wage disparities and changing family composition on the US income distribution, European Economic Review, 43(4–6)(1999), 853–865.
  • Chakraborty, S., Zavadskas, E.K., Applications of WASPAS method in manufacturing decision-making, Informatica, 25(1)(2014), 1–20.
  • Cowell, F., Measuring Inequality, Oxford University Press, 2011.
  • Dabla-Norris, E., Kochhar, K., Suphaphiphat, N., Ricka, F., Tsounta, E., Causes and consequences of income inequality: A global perspective, IMF Staff discussion note No. 15/13, Washington, DC: International Monetary Fund (2015).
  • Deschrijver, G., Cornelis, C., Representabılıty In Interval-Valued Fuzzy Set Theory, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 15(03)(2007), 345–361.
  • Fei, L., Wang, H., Chen, L., Deng, Y., A new vector valued similarity measure for intuitionistic fuzzy sets based on OWA operators, Iranian Journal of Fuzzy Systems, 16(3)(2019), 113–126.
  • Keshavarz Ghorabaee, M., Zavadskas, E.K., Amiri, M., Esmaeili, A., Multi-criteria evaluation of green suppliers using an extended WASPAS method with interval type-2 fuzzy sets, Journal of Cleaner Production, 137(2016), 213–229.
  • Giordani, P., Giorgi, G.M., A fuzzy logic approach to poverty analysis based on the Gini and Bonferroni inequality indices, Statistical Methods and Applications, 19(4)(2010), 587–607.
  • Gini, C., Measurement of inequality of incomes, The economic journal, 31(121)(1921), 124–125.
  • Harsanyi, J.C., Cardinal welfare, individualistic ethics, and interpersonal comparisons of utility, Journal of political economy, 63(4)(1955), 309–321.
  • Hasnoi, L., Belhadj, B., Fuzzy multidimensional inequality measurement. Policies to reduce inequality in Tunisia, EuroEconomica, Danubius University of Galati, 2(34)(2015), 21–28.
  • Hwang, C.L., Yoon, K., Hwang, C.L., Yoon, K., Methods for multiple attribute decision making, Multiple attribute decision making: methods and applications a state-of-the-art survey, (1981), 58–191.
  • Hussain, A., Majeed, S., Shoaib, M., Ali, H., Ullah, K., WASPAS Method for Healthcare Systems based on Intuitionistic Fuzzy Information, (2024).
  • Juhn, C., Murphy, K. M., Pierce, B., Wage inequality and the rise in returns to skill, Journal of political Economy, 101(3)(1993), 410–442.
  • Kaasa, A., Factors of Income Inequality and Their Influence Mechanisms: A Theoretical Overview, University of Tartu Faculty of Economics and Business Administration Working Paper No. 40 , (2005).
  • Kannan, J., Jayakumar, V., Sustainable method for tender selection using linear Diophantine multi-fuzzy soft set, Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics, 72(4)(2023), 976–991.
  • Keeley, B., Income Inequality: The Gap between Rich and Poor, OECD Insights, OECD Publishing, Paris, 2015.
  • Klement, E.P., Mesiar, R., Pap, E., Triangular norms, Kluwer Academic Publishers, Dordrecht, 2002.
  • Klement, E.P., Mesiar, R., Pap, E., Triangular norms. Position paper III: continuous t-norms, Fuzzy Sets and Systems, 145(3)(2004), 439–454.
  • Liu, Y., Xie, N., Amelioration operators of fuzzy number intuitionistic fuzzy geometric and their application to Multi-criteria decision-making, 2009 Chinese Control and Decision Conference (2009).
  • Mishra, A.R., Singh, R.K., Motwani, D., Multi-criteria assessment of cellular mobile telephone service providers using intuitionistic fuzzy WASPAS method with similarity measures, Granular Computing, 4(2018), 511–529.
  • Mishra, A.R., Rani, P., Multi-criteria healthcare waste disposal location selection based on Fermatean fuzzy WASPAS method, Complex and Intelligent Systems, 7(2021), 2469–2484.
  • Morelli, S., Smeeding, T., Thompson, J., Post-1970 Trends in Within-Country Inequality and Poverty, In: Handbook of Income Distribution, 2015.
  • Lakshmana Gomathi Nayagam, V., Muralikrishnan, S., Sivaraman, G., Multi-criteria decision-making method based on interval-valued intuitionistic fuzzy sets, Expert Systems with Applications, 38(3)(2011), 1464–1467.
  • OECD, Income distribution database, Retrieved from https://data-explorer.oecd.org/vis?tm=DF_ IDD&pg=0&snb=1&vw=tb&df[ds]=dsDisseminateFinalDMZ&df[id]=DSD_WISE_IDD%40DF_IDD&df[ag]=OECD.WISE.INE&df[vs]=&pd=2010%2C&dq=.A.INC_DISP..._T.METH2012.D_CUR.&ly[rw]=REF_AREA&ly[cl]=TIME_PERIOD&to[TIME_PERIOD]=false (2025).
  • Ok, E.A., Fuzzy measurement of income inequality: a class of fuzzy inequality measures, Social Choice and Welfare, 12(2)(1995), 111–116.
  • Palma, J.G., Homogeneous middles vs. heterogeneous tails, and the end of the ’inverted-U’: It’s all about the share of the rich, Development and Change, 42(1), 87–153 (2011).
  • Qureshi, Z., Rising Inequality: A Major Issue of our Time, Report, The Brookings Institution, Washington DC (2023).
  • Raj, A.K, Bathusha, S.N.S., Hussain, S., Self centered interval-valued intuitionistic fuzzy graph with an application, Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics, 72(4)(2023), 1155–1172.
  • Reiser, R.H.S., Bedregal, B., Interval-valued intuitionistic fuzzy implications - Construction, properties and representability, Information Sciences, 248(2013), 68–88.
  • Rutkowska, A., Kaczmarek-Majer, K., Bartkowiak, M., Hryniewicz, O., Explaining the relation between life expectancy and income inequality with fuzzy linguistic summaries, (2023).
  • Sen, B., Growth and poverty reduction: macroeconomic experience, In: World Bank, Social Impact of Adjustment Operation, Washington DC: World Bank, Operations and Evaluation Department, 1995.
  • Smarandache, F., A unifying field of logics. Neutrosophy: Neutrosophic probability, set and logic, American Research Press, Rehoboth, 1998.
  • Stewart, F., Income Distribution and Development, In: John Toye ed. Trade and Development, Directions for the Twenty-first Century, Edward Elgar Publishing, 2003.
  • Urosevic, S., Karabasevic, D., Stanujkic, D., Maksimovic, M., An approach to personnel selection in the tourism industry based on the SWARA and the WASPAS methods, Economic Computation and Economic Cybernetics Studies and Research, 51(2017), 75–88.
  • Ünver, M., Gaussian Aggregation Operators and Applications to Intuitionistic Fuzzy Classification, Journal of Classification, (2025).
  • Ünver, M., Türkarslan, E., Çelik, N., Olgun, M., Ye, J., Intuitionistic fuzzy-valued neutrosophic multi-sets and numerical applications to classification, Complex Intell. Syst., 8(2022), 1703–1721.
  • Wang, S.F., Interval-valued intuitionistic fuzzy Choquet integral operators based on Archimedean t-norm and their calculations, Journal of Computational Analysis and Applications, 23(4)(2017), 703–712.
  • Wang, H., Smarandache, F., Zhang, Y., Sunderraman, R., Interval Neutrosophic Sets and Logic: Theory and Applications in Computing, Hexis, Phoenix (2005).
  • Wang, Z., Li, K.W., Wang, W., An approach to multiattribute decision-making with interval-valued intuitionistic fuzzy assessments and incomplete weights, Information Sciences, 179(17)(2009), 3026–3040.
  • Wang, H., Smarandache, F., Zhang, Y. Q., Sunderraman, R., Single valued neutrosophic sets, Multispace Multistruct, 4(2010), 410–413.
  • Wang, W., Liu, X., Qin, Y., Interval-valued intuitionistic fuzzy aggregation operators, Journal of Systems Engineering and Electronics, 23(4)(2012), 574–580.
  • Xia, M., Xu, Z., Zhu, B., Some issues on intuitionistic fuzzy aggregation operators based on Archimedean tconorm and t-norm, Knowledge-Based Systems, 31(2012), 78–88.
  • Xu, Z.S., Methods for aggregating interval-valued intuitionistic fuzzy information and their application to decision-making, Control and Decision, 22(2007), 215–219.
  • Xu, Z.S., Chen, J., An Overview Of Distance And Similarity Measures Of Intuitioistic Fuzzy Sets, International Journal Of Uncertainty, Fuzziness And Knowledge-Based Systems, 16(04)(2008), 529–555.
  • Xu, F., Yin, H.,Wu, Q., An axiomatic approch of interval-valued intuitionistic fuzzy rough sets based on intervalvalued intuitionistic fuzzy approximation operators, 2012 2nd International Conference on Consumer Electronics, Communications and Networks (CECNet) (2012).
  • Yager, R.R., Pythagorean Membership Grades in Multicriteria decision-making, IEEE Transactions on Fuzzy Systems, 22(4)(2014), 958–965.
  • Ye, J., A multicriteria decision-making method using aggregation operators for simplified neutrosophic sets, Journal of Intelligent and Fuzzy Systems, 26(5)(2014), 2459–2466.
  • Zadeh, L.A., Fuzzy sets, Information and Control, 8(3)(1965), 338–353.
  • Zadeh, L., The concept of a linguistic variable and its application to approximate reasoning-I, Inform. Sci., 8(1975), 199–249.
  • Zavadskas, E.K., Kaklauskas, A., Šarka, V., The new method of multicriteria complex proportional assessment of projects, (1994).
  • Zavadskas, E.K., Turskis, Z., Antucheviciene, J., Zakarevicius, A., Optimization of Weighted Aggregated Sum Product Assessment, Elektronika Ir Elektrotechnika, 122(6)(2012), 3–6.

A Novel Interval-Valued Intuitionistic Fuzzy Neutrosophic Framework for Addressing Income Inequality in Multi-Criteria Decision-Making

Year 2025, Volume: 17 Issue: 1, 243 - 263, 30.06.2025
https://doi.org/10.47000/tjmcs.1677588

Abstract

Income equality plays a fundamental role in ensuring sustainable development and social welfare globally. The increase in economic inequality threatens not only the living standards between individuals but also societal harmony and economic stability. In many developed and developing countries, injustices in income distribution exacerbate social tensions and negatively affect long-term economic growth. This study introduces a novel multi-criteria decision-making framework based on interval-valued intuitionistic fuzzy neutrosophic sets (IVIFNSs) to evaluate and compare income equality across selected Organisation for Economic Co-operation and Development (OECD) countries. The IVIFNS model improves traditional fuzzy systems by representing truth, indeterminacy, and falsity degrees with interval-valued intuitionistic fuzzy values, offering a more nuanced approach to uncertainty. Algebraic operations are defined using triangular-norms and triangular-conorms, and new aggregation operators are developed. The proposed theory is applied to rank 25 OECD countries based on key income inequality indicators: Gini coefficient, Palma ratio, P90/P10, and P90/P50, using the Weighted Aggregated Sum Product Assessment (WASPAS) method. A comparative analysis demonstrates the method’s effectiveness in capturing complex, uncertain data and producing robust country rankings for policy evaluation.

References

  • Alvaredo, F., Chancel, L., Piketty, T., Saez, E., Zucman, G., Global Inequality Dynamics: New Findings from WID.world, American Economic Review, 107(5)(2017), 404–409.
  • Ashraf, S., Abdullah, S., Mahmood, T., Ghani, F., Mahmood, T., Spherical fuzzy sets and their applications in multi-attribute decision-making problems, J. Intell. Fuzzy Syst., 36(3)(2019), 2829–2844.
  • Ashraf Ganjoei, R., Akbarifard, H., Mashinchi, M., Jalaee Esfandabadi, S.A., Applying of fuzzy Nonlinear Regression to Investigate the Effect of Information and Communication Technology (ICT) on Income Distribution, vol.2021(2021), 1–11.
  • Atanassov, K.T., Intuitionistic fuzzy sets, In Intuitionistic fuzzy sets, Physica, Heidelberg, 1999.
  • Atanassov, K., Gargov, G., Interval-valued fuzzy set, Fuzzy Sets and Systems, 31, 343–349 (1989).
  • Aydoğan, B., Ünver, M., A modified similarity measure for continuous function valued intuitionistic fuzzy sets and an application on classification, Springer Proceeding in Mathematics and Statistics (accepted).
  • Atkinson, A.B., Income inequality in OECD countries: Data and Explanations, CESifo Economic Studies, 49(4)(2003), 479–513.
  • Bai, Z., An interval-vValued iIntuitionistic fuzzy TOPSIS method based on an improved score function, The Scientific World Journal, 2013(2013), 1–6.
  • Bedregal, B., Lima, L., Rocha, M., Dimuro, G., Bustince, H., Interval-valued Atanassov intuitionistic t-norms and t-conorms endowed with the usual or admissible orders, Comput. Appl. Math., 42(1)(2023), 49.
  • Beliakov, G., Bustince, H., Goswami, D.P., Mukherjee, U.K., Pal, N.R., On averaging operators for Atanassov’s intuitionistic fuzzy sets, Information Sciences, 181(6)(2011), 1116–1124.
  • Bozyiğit, M.C., Olgun, M., Ünver, M., Söylemez, D., Parametric picture fuzzy cross-entropy measures based on d-Choquet integral for building material recognition, Applied Soft Computing, 166(2024), 112167.
  • Bozyigit, M.C., Smarandache, F., Olgun, M., Ünver, M., A new type of neutrosophic set in Pythagorean fuzzy environment and applications to multi-criteria decision-making, International Journal of Neutrosophic Science, 20(2)(2023), 107–134.
  • Burtless, G., Effects of growing wage disparities and changing family composition on the US income distribution, European Economic Review, 43(4–6)(1999), 853–865.
  • Chakraborty, S., Zavadskas, E.K., Applications of WASPAS method in manufacturing decision-making, Informatica, 25(1)(2014), 1–20.
  • Cowell, F., Measuring Inequality, Oxford University Press, 2011.
  • Dabla-Norris, E., Kochhar, K., Suphaphiphat, N., Ricka, F., Tsounta, E., Causes and consequences of income inequality: A global perspective, IMF Staff discussion note No. 15/13, Washington, DC: International Monetary Fund (2015).
  • Deschrijver, G., Cornelis, C., Representabılıty In Interval-Valued Fuzzy Set Theory, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 15(03)(2007), 345–361.
  • Fei, L., Wang, H., Chen, L., Deng, Y., A new vector valued similarity measure for intuitionistic fuzzy sets based on OWA operators, Iranian Journal of Fuzzy Systems, 16(3)(2019), 113–126.
  • Keshavarz Ghorabaee, M., Zavadskas, E.K., Amiri, M., Esmaeili, A., Multi-criteria evaluation of green suppliers using an extended WASPAS method with interval type-2 fuzzy sets, Journal of Cleaner Production, 137(2016), 213–229.
  • Giordani, P., Giorgi, G.M., A fuzzy logic approach to poverty analysis based on the Gini and Bonferroni inequality indices, Statistical Methods and Applications, 19(4)(2010), 587–607.
  • Gini, C., Measurement of inequality of incomes, The economic journal, 31(121)(1921), 124–125.
  • Harsanyi, J.C., Cardinal welfare, individualistic ethics, and interpersonal comparisons of utility, Journal of political economy, 63(4)(1955), 309–321.
  • Hasnoi, L., Belhadj, B., Fuzzy multidimensional inequality measurement. Policies to reduce inequality in Tunisia, EuroEconomica, Danubius University of Galati, 2(34)(2015), 21–28.
  • Hwang, C.L., Yoon, K., Hwang, C.L., Yoon, K., Methods for multiple attribute decision making, Multiple attribute decision making: methods and applications a state-of-the-art survey, (1981), 58–191.
  • Hussain, A., Majeed, S., Shoaib, M., Ali, H., Ullah, K., WASPAS Method for Healthcare Systems based on Intuitionistic Fuzzy Information, (2024).
  • Juhn, C., Murphy, K. M., Pierce, B., Wage inequality and the rise in returns to skill, Journal of political Economy, 101(3)(1993), 410–442.
  • Kaasa, A., Factors of Income Inequality and Their Influence Mechanisms: A Theoretical Overview, University of Tartu Faculty of Economics and Business Administration Working Paper No. 40 , (2005).
  • Kannan, J., Jayakumar, V., Sustainable method for tender selection using linear Diophantine multi-fuzzy soft set, Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics, 72(4)(2023), 976–991.
  • Keeley, B., Income Inequality: The Gap between Rich and Poor, OECD Insights, OECD Publishing, Paris, 2015.
  • Klement, E.P., Mesiar, R., Pap, E., Triangular norms, Kluwer Academic Publishers, Dordrecht, 2002.
  • Klement, E.P., Mesiar, R., Pap, E., Triangular norms. Position paper III: continuous t-norms, Fuzzy Sets and Systems, 145(3)(2004), 439–454.
  • Liu, Y., Xie, N., Amelioration operators of fuzzy number intuitionistic fuzzy geometric and their application to Multi-criteria decision-making, 2009 Chinese Control and Decision Conference (2009).
  • Mishra, A.R., Singh, R.K., Motwani, D., Multi-criteria assessment of cellular mobile telephone service providers using intuitionistic fuzzy WASPAS method with similarity measures, Granular Computing, 4(2018), 511–529.
  • Mishra, A.R., Rani, P., Multi-criteria healthcare waste disposal location selection based on Fermatean fuzzy WASPAS method, Complex and Intelligent Systems, 7(2021), 2469–2484.
  • Morelli, S., Smeeding, T., Thompson, J., Post-1970 Trends in Within-Country Inequality and Poverty, In: Handbook of Income Distribution, 2015.
  • Lakshmana Gomathi Nayagam, V., Muralikrishnan, S., Sivaraman, G., Multi-criteria decision-making method based on interval-valued intuitionistic fuzzy sets, Expert Systems with Applications, 38(3)(2011), 1464–1467.
  • OECD, Income distribution database, Retrieved from https://data-explorer.oecd.org/vis?tm=DF_ IDD&pg=0&snb=1&vw=tb&df[ds]=dsDisseminateFinalDMZ&df[id]=DSD_WISE_IDD%40DF_IDD&df[ag]=OECD.WISE.INE&df[vs]=&pd=2010%2C&dq=.A.INC_DISP..._T.METH2012.D_CUR.&ly[rw]=REF_AREA&ly[cl]=TIME_PERIOD&to[TIME_PERIOD]=false (2025).
  • Ok, E.A., Fuzzy measurement of income inequality: a class of fuzzy inequality measures, Social Choice and Welfare, 12(2)(1995), 111–116.
  • Palma, J.G., Homogeneous middles vs. heterogeneous tails, and the end of the ’inverted-U’: It’s all about the share of the rich, Development and Change, 42(1), 87–153 (2011).
  • Qureshi, Z., Rising Inequality: A Major Issue of our Time, Report, The Brookings Institution, Washington DC (2023).
  • Raj, A.K, Bathusha, S.N.S., Hussain, S., Self centered interval-valued intuitionistic fuzzy graph with an application, Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics, 72(4)(2023), 1155–1172.
  • Reiser, R.H.S., Bedregal, B., Interval-valued intuitionistic fuzzy implications - Construction, properties and representability, Information Sciences, 248(2013), 68–88.
  • Rutkowska, A., Kaczmarek-Majer, K., Bartkowiak, M., Hryniewicz, O., Explaining the relation between life expectancy and income inequality with fuzzy linguistic summaries, (2023).
  • Sen, B., Growth and poverty reduction: macroeconomic experience, In: World Bank, Social Impact of Adjustment Operation, Washington DC: World Bank, Operations and Evaluation Department, 1995.
  • Smarandache, F., A unifying field of logics. Neutrosophy: Neutrosophic probability, set and logic, American Research Press, Rehoboth, 1998.
  • Stewart, F., Income Distribution and Development, In: John Toye ed. Trade and Development, Directions for the Twenty-first Century, Edward Elgar Publishing, 2003.
  • Urosevic, S., Karabasevic, D., Stanujkic, D., Maksimovic, M., An approach to personnel selection in the tourism industry based on the SWARA and the WASPAS methods, Economic Computation and Economic Cybernetics Studies and Research, 51(2017), 75–88.
  • Ünver, M., Gaussian Aggregation Operators and Applications to Intuitionistic Fuzzy Classification, Journal of Classification, (2025).
  • Ünver, M., Türkarslan, E., Çelik, N., Olgun, M., Ye, J., Intuitionistic fuzzy-valued neutrosophic multi-sets and numerical applications to classification, Complex Intell. Syst., 8(2022), 1703–1721.
  • Wang, S.F., Interval-valued intuitionistic fuzzy Choquet integral operators based on Archimedean t-norm and their calculations, Journal of Computational Analysis and Applications, 23(4)(2017), 703–712.
  • Wang, H., Smarandache, F., Zhang, Y., Sunderraman, R., Interval Neutrosophic Sets and Logic: Theory and Applications in Computing, Hexis, Phoenix (2005).
  • Wang, Z., Li, K.W., Wang, W., An approach to multiattribute decision-making with interval-valued intuitionistic fuzzy assessments and incomplete weights, Information Sciences, 179(17)(2009), 3026–3040.
  • Wang, H., Smarandache, F., Zhang, Y. Q., Sunderraman, R., Single valued neutrosophic sets, Multispace Multistruct, 4(2010), 410–413.
  • Wang, W., Liu, X., Qin, Y., Interval-valued intuitionistic fuzzy aggregation operators, Journal of Systems Engineering and Electronics, 23(4)(2012), 574–580.
  • Xia, M., Xu, Z., Zhu, B., Some issues on intuitionistic fuzzy aggregation operators based on Archimedean tconorm and t-norm, Knowledge-Based Systems, 31(2012), 78–88.
  • Xu, Z.S., Methods for aggregating interval-valued intuitionistic fuzzy information and their application to decision-making, Control and Decision, 22(2007), 215–219.
  • Xu, Z.S., Chen, J., An Overview Of Distance And Similarity Measures Of Intuitioistic Fuzzy Sets, International Journal Of Uncertainty, Fuzziness And Knowledge-Based Systems, 16(04)(2008), 529–555.
  • Xu, F., Yin, H.,Wu, Q., An axiomatic approch of interval-valued intuitionistic fuzzy rough sets based on intervalvalued intuitionistic fuzzy approximation operators, 2012 2nd International Conference on Consumer Electronics, Communications and Networks (CECNet) (2012).
  • Yager, R.R., Pythagorean Membership Grades in Multicriteria decision-making, IEEE Transactions on Fuzzy Systems, 22(4)(2014), 958–965.
  • Ye, J., A multicriteria decision-making method using aggregation operators for simplified neutrosophic sets, Journal of Intelligent and Fuzzy Systems, 26(5)(2014), 2459–2466.
  • Zadeh, L.A., Fuzzy sets, Information and Control, 8(3)(1965), 338–353.
  • Zadeh, L., The concept of a linguistic variable and its application to approximate reasoning-I, Inform. Sci., 8(1975), 199–249.
  • Zavadskas, E.K., Kaklauskas, A., Šarka, V., The new method of multicriteria complex proportional assessment of projects, (1994).
  • Zavadskas, E.K., Turskis, Z., Antucheviciene, J., Zakarevicius, A., Optimization of Weighted Aggregated Sum Product Assessment, Elektronika Ir Elektrotechnika, 122(6)(2012), 3–6.
There are 64 citations in total.

Details

Primary Language English
Subjects Mathematical Logic, Set Theory, Lattices and Universal Algebra, Operations Research İn Mathematics
Journal Section Articles
Authors

Nazlı Büşra Karaoğlu 0009-0009-4310-1024

Mehmet Ünver 0000-0002-0857-1006

Murat Olgun 0000-0002-8660-5435

Publication Date June 30, 2025
Submission Date April 16, 2025
Acceptance Date June 11, 2025
Published in Issue Year 2025 Volume: 17 Issue: 1

Cite

APA Karaoğlu, N. B., Ünver, M., & Olgun, M. (2025). A Novel Interval-Valued Intuitionistic Fuzzy Neutrosophic Framework for Addressing Income Inequality in Multi-Criteria Decision-Making. Turkish Journal of Mathematics and Computer Science, 17(1), 243-263. https://doi.org/10.47000/tjmcs.1677588
AMA Karaoğlu NB, Ünver M, Olgun M. A Novel Interval-Valued Intuitionistic Fuzzy Neutrosophic Framework for Addressing Income Inequality in Multi-Criteria Decision-Making. TJMCS. June 2025;17(1):243-263. doi:10.47000/tjmcs.1677588
Chicago Karaoğlu, Nazlı Büşra, Mehmet Ünver, and Murat Olgun. “A Novel Interval-Valued Intuitionistic Fuzzy Neutrosophic Framework for Addressing Income Inequality in Multi-Criteria Decision-Making”. Turkish Journal of Mathematics and Computer Science 17, no. 1 (June 2025): 243-63. https://doi.org/10.47000/tjmcs.1677588.
EndNote Karaoğlu NB, Ünver M, Olgun M (June 1, 2025) A Novel Interval-Valued Intuitionistic Fuzzy Neutrosophic Framework for Addressing Income Inequality in Multi-Criteria Decision-Making. Turkish Journal of Mathematics and Computer Science 17 1 243–263.
IEEE N. B. Karaoğlu, M. Ünver, and M. Olgun, “A Novel Interval-Valued Intuitionistic Fuzzy Neutrosophic Framework for Addressing Income Inequality in Multi-Criteria Decision-Making”, TJMCS, vol. 17, no. 1, pp. 243–263, 2025, doi: 10.47000/tjmcs.1677588.
ISNAD Karaoğlu, Nazlı Büşra et al. “A Novel Interval-Valued Intuitionistic Fuzzy Neutrosophic Framework for Addressing Income Inequality in Multi-Criteria Decision-Making”. Turkish Journal of Mathematics and Computer Science 17/1 (June2025), 243-263. https://doi.org/10.47000/tjmcs.1677588.
JAMA Karaoğlu NB, Ünver M, Olgun M. A Novel Interval-Valued Intuitionistic Fuzzy Neutrosophic Framework for Addressing Income Inequality in Multi-Criteria Decision-Making. TJMCS. 2025;17:243–263.
MLA Karaoğlu, Nazlı Büşra et al. “A Novel Interval-Valued Intuitionistic Fuzzy Neutrosophic Framework for Addressing Income Inequality in Multi-Criteria Decision-Making”. Turkish Journal of Mathematics and Computer Science, vol. 17, no. 1, 2025, pp. 243-6, doi:10.47000/tjmcs.1677588.
Vancouver Karaoğlu NB, Ünver M, Olgun M. A Novel Interval-Valued Intuitionistic Fuzzy Neutrosophic Framework for Addressing Income Inequality in Multi-Criteria Decision-Making. TJMCS. 2025;17(1):243-6.