How to cite this paper
Sotoudeh-Anvari, A. (2019). A short note on methods of ranking fuzzy numbers in risk analysis problems.Journal of Project Management, 4(3), 229-232.
Refrences
Akyar, E., Akyar, H., & Düzce, S. A. (2013). Fuzzy risk analysis based on a geometric ranking method for generalized trapezoidal fuzzy numbers. Journal of Intelligent & Fuzzy Sys-tems, 25(1), 209-217.
Alidoosti, A., Jamshidi, A., Yakhchali, S., Basiri, M., Azizi, R., & Yazdani-Chamzini, A. (2012). Fuzzy logic for pipelines risk assessment. Management Science Letters, 2(5), 1707-1716.
Chen, S. J., & Chen, S. M. (2003). Fuzzy risk analysis based on similarity measures of generalized fuzzy numbers. IEEE Transactions on fuzzy systems, 11(1), 45-56.
Chen, S. J., & Chen, S. M. (2007). Fuzzy risk analysis based on the ranking of generalized trape-zoidal fuzzy numbers. Applied intelligence, 26(1), 1-11.
Chen, S. J., & Chen, S. M. (2008). Fuzzy risk analysis based on measures of similarity between in-terval-valued fuzzy numbers. Computers & Mathematics with Applications, 55(8), 1670-1685.
Chen, S. M., & Chen, J. H. (2009). Fuzzy risk analysis based on ranking generalized fuzzy num-bers with different heights and different spreads. Expert systems with applications, 36(3), 6833-6842.
Chen, S. M., Munif, A., Chen, G. S., Liu, H. C., & Kuo, B. C. (2012). Fuzzy risk analysis based on ranking generalized fuzzy numbers with different left heights and right heights. Expert Sys-tems with Applications, 39(7), 6320-6334.
Chen, S. M., & Sanguansat, K. (2011). Analyzing fuzzy risk based on a new fuzzy ranking meth-od between generalized fuzzy numbers. Expert Systems with Applications, 38(3), 2163-2171.
Chen, S. M., & Wang, C. H. (2009). Fuzzy risk analysis based on ranking fuzzy numbers using α-cuts, belief features and signal/noise ratios. Expert systems with applications, 36(3), 5576-5581.
Jiang, W., Luo, Y., Qin, X. Y., & Zhan, J. (2015). An improved method to rank generalized fuzzy numbers with different left heights and right heights. Journal of Intelligent & Fuzzy Sys-tems, 28(5), 2343-2355.
Kumar, A., Singh, P., Kaur, P., & Kaur, A. (2011). A new approach for ranking of L–R type gen-eralized fuzzy numbers. Expert Systems with Applications, 38(9), 10906-10910.
Lee, L. W., & Chen, S. M. (2008). Fuzzy risk analysis based on fuzzy numbers with different shapes and different deviations. Expert Systems with Applications, 34(4), 2763-2771.
Liou, T. S., & Wang, M. J. J. (1992). Ranking fuzzy numbers with integral value. Fuzzy Sets and Systems, 50(3), 247-255.
Madhuri, K. U., Babu, S. S., & Shankar, N. R. (2014). Fuzzy risk analysis based on the novel fuzzy ranking with new arithmetic operations of linguistic fuzzy numbers. Journal of Intelligent & Fuzzy Systems, 26(5), 2391-2401.
Motawa, I. A., Anumba, C. J., & El-Hamalawi, A. (2006). A fuzzy system for evaluating the risk of change in construction projects. Advances in Engineering Software, 37(9), 583-591.
Ngai, E. W., & Wat, F. K. T. (2005). Fuzzy decision support system for risk analysis in e-commerce development. Decision Support Systems, 40(2), 235-255.
Nieto-Morote, A., & Ruz-Vila, F. (2011). A fuzzy approach to construction project risk assess-ment. International Journal of Project Management, 29(2), 220-231.
Perminova, O., Gustafsson, M., & Wikström, K. (2008). Defining uncertainty in projects–a new perspective. International Journal of Project Management, 26(1), 73-79.
Sotoudeh-Anvari, A. (2016). Comparing trapezoidal fuzzy numbers by using a hybrid technique on the base of the ideal points and the centroid point. Journal of Intelligent & Fuzzy Sys-tems, 30(6), 3099-3109.
Sotoudeh-Anvari, A., Sadjadi, S. J., & Sadi-Nezhad, S. (2017). Theoretical Drawbacks in Fuzzy Ranking Methods and Some Suggestions for a Meaningful Comparison: An Application to Fuzzy Risk Analysis. Cybernetics and Systems, 48(8), 551-575.
Wang, X., & Kerre, E. E. (2001). Reasonable properties for the ordering of fuzzy quantities (I). Fuzzy sets and systems, 118(3), 375-385.
Wei, S. H., & Chen, S. M. (2009a). Fuzzy risk analysis based on interval-valued fuzzy num-bers. Expert Systems with Applications, 36(2), 2285-2299.
Wei, S. H., & Chen, S. M. (2009b). A new approach for fuzzy risk analysis based on similarity measures of generalized fuzzy numbers. Expert Systems with Applications, 36(1), 589-598.
Xu, Z., Shang, S., Qian, W., & Shu, W. (2010). A method for fuzzy risk analysis based on the new similarity of trapezoidal fuzzy numbers. Expert Systems with Applications, 37(3), 1920-1927.
Zadeh, L. A. (1965). Fuzzy sets. Information and control, 8(3), 338-353.
Zhü, K. (2014). Fuzzy analytic hierarchy process: Fallacy of the popular methods. European Jour-nal of Operational Research, 236(1), 209-217.
Alidoosti, A., Jamshidi, A., Yakhchali, S., Basiri, M., Azizi, R., & Yazdani-Chamzini, A. (2012). Fuzzy logic for pipelines risk assessment. Management Science Letters, 2(5), 1707-1716.
Chen, S. J., & Chen, S. M. (2003). Fuzzy risk analysis based on similarity measures of generalized fuzzy numbers. IEEE Transactions on fuzzy systems, 11(1), 45-56.
Chen, S. J., & Chen, S. M. (2007). Fuzzy risk analysis based on the ranking of generalized trape-zoidal fuzzy numbers. Applied intelligence, 26(1), 1-11.
Chen, S. J., & Chen, S. M. (2008). Fuzzy risk analysis based on measures of similarity between in-terval-valued fuzzy numbers. Computers & Mathematics with Applications, 55(8), 1670-1685.
Chen, S. M., & Chen, J. H. (2009). Fuzzy risk analysis based on ranking generalized fuzzy num-bers with different heights and different spreads. Expert systems with applications, 36(3), 6833-6842.
Chen, S. M., Munif, A., Chen, G. S., Liu, H. C., & Kuo, B. C. (2012). Fuzzy risk analysis based on ranking generalized fuzzy numbers with different left heights and right heights. Expert Sys-tems with Applications, 39(7), 6320-6334.
Chen, S. M., & Sanguansat, K. (2011). Analyzing fuzzy risk based on a new fuzzy ranking meth-od between generalized fuzzy numbers. Expert Systems with Applications, 38(3), 2163-2171.
Chen, S. M., & Wang, C. H. (2009). Fuzzy risk analysis based on ranking fuzzy numbers using α-cuts, belief features and signal/noise ratios. Expert systems with applications, 36(3), 5576-5581.
Jiang, W., Luo, Y., Qin, X. Y., & Zhan, J. (2015). An improved method to rank generalized fuzzy numbers with different left heights and right heights. Journal of Intelligent & Fuzzy Sys-tems, 28(5), 2343-2355.
Kumar, A., Singh, P., Kaur, P., & Kaur, A. (2011). A new approach for ranking of L–R type gen-eralized fuzzy numbers. Expert Systems with Applications, 38(9), 10906-10910.
Lee, L. W., & Chen, S. M. (2008). Fuzzy risk analysis based on fuzzy numbers with different shapes and different deviations. Expert Systems with Applications, 34(4), 2763-2771.
Liou, T. S., & Wang, M. J. J. (1992). Ranking fuzzy numbers with integral value. Fuzzy Sets and Systems, 50(3), 247-255.
Madhuri, K. U., Babu, S. S., & Shankar, N. R. (2014). Fuzzy risk analysis based on the novel fuzzy ranking with new arithmetic operations of linguistic fuzzy numbers. Journal of Intelligent & Fuzzy Systems, 26(5), 2391-2401.
Motawa, I. A., Anumba, C. J., & El-Hamalawi, A. (2006). A fuzzy system for evaluating the risk of change in construction projects. Advances in Engineering Software, 37(9), 583-591.
Ngai, E. W., & Wat, F. K. T. (2005). Fuzzy decision support system for risk analysis in e-commerce development. Decision Support Systems, 40(2), 235-255.
Nieto-Morote, A., & Ruz-Vila, F. (2011). A fuzzy approach to construction project risk assess-ment. International Journal of Project Management, 29(2), 220-231.
Perminova, O., Gustafsson, M., & Wikström, K. (2008). Defining uncertainty in projects–a new perspective. International Journal of Project Management, 26(1), 73-79.
Sotoudeh-Anvari, A. (2016). Comparing trapezoidal fuzzy numbers by using a hybrid technique on the base of the ideal points and the centroid point. Journal of Intelligent & Fuzzy Sys-tems, 30(6), 3099-3109.
Sotoudeh-Anvari, A., Sadjadi, S. J., & Sadi-Nezhad, S. (2017). Theoretical Drawbacks in Fuzzy Ranking Methods and Some Suggestions for a Meaningful Comparison: An Application to Fuzzy Risk Analysis. Cybernetics and Systems, 48(8), 551-575.
Wang, X., & Kerre, E. E. (2001). Reasonable properties for the ordering of fuzzy quantities (I). Fuzzy sets and systems, 118(3), 375-385.
Wei, S. H., & Chen, S. M. (2009a). Fuzzy risk analysis based on interval-valued fuzzy num-bers. Expert Systems with Applications, 36(2), 2285-2299.
Wei, S. H., & Chen, S. M. (2009b). A new approach for fuzzy risk analysis based on similarity measures of generalized fuzzy numbers. Expert Systems with Applications, 36(1), 589-598.
Xu, Z., Shang, S., Qian, W., & Shu, W. (2010). A method for fuzzy risk analysis based on the new similarity of trapezoidal fuzzy numbers. Expert Systems with Applications, 37(3), 1920-1927.
Zadeh, L. A. (1965). Fuzzy sets. Information and control, 8(3), 338-353.
Zhü, K. (2014). Fuzzy analytic hierarchy process: Fallacy of the popular methods. European Jour-nal of Operational Research, 236(1), 209-217.