A q-rung orthopair fuzzy GLDS method for investment evaluation of BE angel capital in China
Abstract
As a generalized form of both intuitionistic fuzzy set and Pythagorean fuzzy sets, the q-rung orthopair fuzzy set (q-ROFS) has strong ability to handle uncertain or imprecision decisionmaking problems. This paper aims to introduce a new multiple criteria decision making method based on the original gain and lost dominance score (GLDS) method for investment evaluation. To do so, we first propose a new distance measure of q-rung orthopair fuzzy numbers (q-ROFNs), which takes into account the hesitancy degree of q-ROFNs. Subsequently, two methods are developed to determine the weights of DMs and criteria, respectively. Next, the original GLDS method is improved from the aspects of dominance flows and order scores of alternatives to address the multiple criteria decision making problems with q-ROFS information. Finally, a case study concerning the investment evaluation of the BE angle capital is given to illustrate the applicability and superiority of the proposed method.
Keyword : investment evaluation, multiple criteria decision making, gained and lost dominance score method, q-rung orthopair fuzzy sets, distance measure, weight determination
How to Cite
Liao, H., Zhang, H., Zhang, C., Wu, X., Mardani, A., & Al-Barakati, A. (2020). A q-rung orthopair fuzzy GLDS method for investment evaluation of BE angel capital in China. Technological and Economic Development of Economy, 26(1), 103-134. https://doi.org/10.3846/tede.2020.11260
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Pamučar, D., Božanić, D., & Ranđelović, A. (2017). Multi-criteria decision making: An example of sensitivity analysis. Serbian Journal of Management, 12(1), 1-27. http://doi.org/10.5937/sjm12-9464
Pamučar, D., Sremac, S., Stević, Ž., Ćirović, G., & Tomić, D. (2019). New multi-criteria LNN WASPAS model for evaluating the work of advisors in the transport of hazardous goods. Neural Computing and Applications, 31(9), 5045-5068. https://doi.org/10.1007/s00521-018-03997-7
Peng, X. D., Dai, J. G., & Garg, H. (2018). Exponential operation and aggregation operator for q-rung orthopair fuzzy set and their decision-making method with a new score function. International Journal of Intelligent Systems, 33, 2255-2282. https://doi.org/10.1002/int.22028
Szmidt, E., & Kacprzyk, J. (2000). Distances between intuitionistic fuzzy sets. Fuzzy Sets and Systems, 114, 505-518. https://doi.org/10.1016/s0165-0114(98)00244-9
Wang, Y. M. (1997). Using the method of maximizing deviations to make decision for multi-indices. Journal of System Engineering and Electronics, 8(3), 21-26. Retrieved from https://ieeexplore.ieee.org/abstract/document/6079108
Wang, J., Zhang, R. T., Zhu, X. M., Zhou, Z., Shang, X. P., & Li, W. Z. (2019). Some q-rung orthopair fuzzy Muirhead means with their application to multi-attribute group decision making. Journal of Intelligent and Fuzzy Systems, 36(2), 1599-1614. https://doi.org/10.3233/JIFS-18607
Wei, G. W., Gao, H., & Wei, Y. (2018). Some q-rung orthopair fuzzy Heronian mean operators in multiple attribute decision making. International Journal of Intelligent Systems, 33, 1426-1458. https://doi.org/10.1002/int.21927
Wu, X. L., & Liao, H. C. (2019). A consensus-based probabilistic linguistic gained and lost dominance score method. European Journal of Operational Research, 272(3), 1017-1027. https://doi.org/10.1016/j.ejor.2018.07.044
Yager, R. R. (2014). Pythagorean membership grades in multicriteria decision making. IEEE Transactions on Fuzzy Systems, 22, 958-965. https://doi.org/10.1109/tfuzz.2013.2278989
Yager, R. R. (2017). Generalized orthopair fuzzy sets. IEEE Transactions on Fuzzy Systems, 25, 12221230. https://doi.org/10.1109/tfuzz.2016.2604005
Yue, Z. L. (2011). A method for group decision-making based on determining weights of decision makers using TOPSIS. Applied Mathematical Modelling, 35, 1926-1936. https://doi.org/10.1016/j.apm.2010.11.001
Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338-353. https://doi.org/10.1016/S0019-9958(65)90241-X
Zhang, X. L., & Xu, Z. S. (2014). Extension of TOPSIS to multiple criteria decision making with Pythagorean fuzzy sets. International Journal of Intelligent Systems, 29, 1061-1078. https://doi.org/10.1002/int.21676
Zhang, Y. X., Xu, Z. S., & Liao, H. C. (2019). Water security evaluation based on the TODIM method with probabilistic linguistic terms set. Soft Computing, 23(15), 6215-6230. https://doi.org/10.1007/s00500-018-3276-9
Du, W. S. (2018a). Minkowski‐type distance measures for generalized orthopair fuzzy sets. International Journal of Intelligent Systems, 3, 802-817. https://doi.org/10.1002/int.21968
Du, W. S. (2018b). Correlation and correlation coefficient of generalized orthopair fuzzy sets. International Journal of Intelligent Systems, 34(4), 564-583. https://doi.org/10.1002/int.22065
Fu, Z. G., Wu, X. L., Liao, H. C., & Herrera, F. (2018). Underground mining method selection with the hesitant fuzzy linguistic gained and lost dominance score method. IEEE Access, 6(1), 66442-66458. https://doi.org/10.1109/access.2018.2878784
Gao, J., Liang, Z. L., Shang, J., & Xu, Z. S. (2018). Continuities, derivatives and differentials of q-rung orthopair fuzzy functions. IEEE Transactions on Fuzzy Systems, 27(8), 1687-1699. https://doi.org/10.1109/tfuzz.2018.2887187
Joshi, B. P., Singh, A., Bhatt, P. K., & Vaisla, K. S. (2018). Interval valued q-rung orthopair fuzzy sets and their properties. Journal of Intelligent and Fuzzy Systems, 35(5), 5225-5230. https://doi.org/10.3233/jifs-169806
Kahneman, D., & Tversky, A. (2013). Prospect theory: An analysis of decision under risk. In Handbook of the fundamentals of financial decision making (part I, pp. 99-127). World Scientific. https://doi.org/10.1142/9789814417358_0006
Li, D. Q., & Zeng, W. Y. (2018). Distance measure of Pythagorean fuzzy sets. International Journal of Intelligent Systems, 33, 348-361. https://doi.org/10.1002/int.21934
Liao, H. C., Jiang, L. S., Xu, Z. S., Xu, J. P., & Herrera, F. (2017). A linear programming method for multiple criteria decision making with probabilistic linguistic information. Information Sciences, 415-416, 341-355. https://doi.org/10.1016/j.ins.2017.06.035
Liao, H. C., Wu, D., Huang, Y. L., Ren, P. J., Xu, Z. S., & Verma, M. (2018a). Green logistic provider selection with a hesitant fuzzy linguistic thermodynamic method integrating prospect theory and PROMETHEE. Sustainability, 10(4), 1291. https://doi.org/10.3390/su10041291
Liao, H. C., Xu, Z. S., Herrera-Viedma, E., & Herrera, F. (2018b). Hesitant fuzzy linguistic term set and its application in decision making: A state-of-the art survey. International Journal of Fuzzy Systems, 20(7), 2084-2110. https://doi.org/10.1007/s40815-017-0432-9
Liu, F., Aiwu, G., Lukovac, V., & Vukic, M. (2018a). A multicriteria model for the selection of the transport service provider: A single valued neutrosophic DEMATEL multicriteria model. Decision Making: Application in Management and Engineering, 1(2), 121-130. https://doi.org/10.31181/dmame1802128l
Liu, P. D., Chen, X. M., & Wang, P. (2018b). Multiple-attribute group decision-making based on q-rung orthopair fuzzy power Maclaurin symmetric mean operators. IEEE Transactions on Fuzzy Systems, 1-16. https://doi.org/10.1109/TSMC.2018.2852948
Liu, W. S., & Liao, H. C. (2017). A bibliometric analysis of fuzzy decision research during 1970-2015. International Journal of Fuzzy Systems, 19(1), 1-14. https://doi.org/10.1007/s40815-016-0272-z
Liu, P. D., & Liu, J. L. (2018). Some q-rung orthopair fuzzy Bonferroni mean operators and their application to multi-attribute group decision making. International Journal of Intelligent Systems, 33(2), 315-347. https://doi.org/10.1002/int.21933
Liu, P. D., & Wang, P. (2018). Some q-rung orthopair fuzzy aggregation operators and their applications to multiple-attribute decision making. International Journal of Intelligent Systems, 33(2), 259-280. https://doi.org/10.1002/int.21927
Liu, P. D., & Wang, P. (2019). Multiple-attribute decision making based on Archimedean Bonferroni operators of q-rung orthopair fuzzy numbers. IEEE Transactions on Fuzzy Systems, 27(5), 834-848. https://doi.org/10.1109/TFUZZ.2018.2826452
Mukhametzyanov, I., & Pamucar, D. (2018). A sensitivity analysis in MCDM problems: A statistical approach. Decision Making: Applications in Management and Engineering, 1(2), 51-80. https://doi.org/10.31181/dmame1802050m
Pamučar, D., Badi, I., Sanja, K., & Obradović, R. (2018). A novel approach for the selection of powergeneration technology using a linguistic neutrosophic CODAS method: A case study in Libya. Energies, 11(9), 2489. https://doi.org/10.3390/en11092489
Pamučar, D., Božanić, D., & Ranđelović, A. (2017). Multi-criteria decision making: An example of sensitivity analysis. Serbian Journal of Management, 12(1), 1-27. http://doi.org/10.5937/sjm12-9464
Pamučar, D., Sremac, S., Stević, Ž., Ćirović, G., & Tomić, D. (2019). New multi-criteria LNN WASPAS model for evaluating the work of advisors in the transport of hazardous goods. Neural Computing and Applications, 31(9), 5045-5068. https://doi.org/10.1007/s00521-018-03997-7
Peng, X. D., Dai, J. G., & Garg, H. (2018). Exponential operation and aggregation operator for q-rung orthopair fuzzy set and their decision-making method with a new score function. International Journal of Intelligent Systems, 33, 2255-2282. https://doi.org/10.1002/int.22028
Szmidt, E., & Kacprzyk, J. (2000). Distances between intuitionistic fuzzy sets. Fuzzy Sets and Systems, 114, 505-518. https://doi.org/10.1016/s0165-0114(98)00244-9
Wang, Y. M. (1997). Using the method of maximizing deviations to make decision for multi-indices. Journal of System Engineering and Electronics, 8(3), 21-26. Retrieved from https://ieeexplore.ieee.org/abstract/document/6079108
Wang, J., Zhang, R. T., Zhu, X. M., Zhou, Z., Shang, X. P., & Li, W. Z. (2019). Some q-rung orthopair fuzzy Muirhead means with their application to multi-attribute group decision making. Journal of Intelligent and Fuzzy Systems, 36(2), 1599-1614. https://doi.org/10.3233/JIFS-18607
Wei, G. W., Gao, H., & Wei, Y. (2018). Some q-rung orthopair fuzzy Heronian mean operators in multiple attribute decision making. International Journal of Intelligent Systems, 33, 1426-1458. https://doi.org/10.1002/int.21927
Wu, X. L., & Liao, H. C. (2019). A consensus-based probabilistic linguistic gained and lost dominance score method. European Journal of Operational Research, 272(3), 1017-1027. https://doi.org/10.1016/j.ejor.2018.07.044
Yager, R. R. (2014). Pythagorean membership grades in multicriteria decision making. IEEE Transactions on Fuzzy Systems, 22, 958-965. https://doi.org/10.1109/tfuzz.2013.2278989
Yager, R. R. (2017). Generalized orthopair fuzzy sets. IEEE Transactions on Fuzzy Systems, 25, 12221230. https://doi.org/10.1109/tfuzz.2016.2604005
Yue, Z. L. (2011). A method for group decision-making based on determining weights of decision makers using TOPSIS. Applied Mathematical Modelling, 35, 1926-1936. https://doi.org/10.1016/j.apm.2010.11.001
Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338-353. https://doi.org/10.1016/S0019-9958(65)90241-X
Zhang, X. L., & Xu, Z. S. (2014). Extension of TOPSIS to multiple criteria decision making with Pythagorean fuzzy sets. International Journal of Intelligent Systems, 29, 1061-1078. https://doi.org/10.1002/int.21676
Zhang, Y. X., Xu, Z. S., & Liao, H. C. (2019). Water security evaluation based on the TODIM method with probabilistic linguistic terms set. Soft Computing, 23(15), 6215-6230. https://doi.org/10.1007/s00500-018-3276-9