A Comparative Study of FCSM, FSAW and TOPSIS Techniques using Triangular Fuzzy Numbers
Keywords:
Fuzzy Multiple Criteria Expert Decision-Making (FMCEDM), fuzzy simple additive weighting, fuzzy cosine similarity measures, technique for order performance by similarity to ideal solution
Abstract
Abstract Views: 162
This paper presents a comparative study of different techniques used for fuzzy multi-criteria expert’s decision-making (FMCEDM). These include CSM1, CSM2, CSM3, FSAW, and TOPSIS. We developed the methods CSM1 and CSM3 respectively and studied their validity by comparing their illustration results with that of CSM2, FSAW and TOPSIS. Expert’s ratings and weights were assigned in linguistic variables in terms of triangular fuzzy numbers (TFNs) to the FMCEDM problem. Airport performance evaluation and a personnel selection problem were studied as alternatives under different decision criteria and experts.
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References
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[22] Zulqarnain RM, Xin XL, Saeed M, Ahmed N. Recruitment of Medical Staff in Health Department by Using TOPSIS Method. Int J Pharma Sci Rev Res. 2020;62(1):1-7.
[23] Zulqarnain M, Dayan F. Selection of best alternative for an automotive company by intuitionistic fuzzy TOPSIS method. Int J Sci Technol Res. 2017 Oct;6(10).
[24] Saeed M, Ali U, Ali J, Dayan F. Fuzzy Soft Relative Method and its Application in Decision Making Problem. Proceedings of the Pakistan Academy of Sciences: A. Physical and Computational Sciences. 2020 Oct 12;57(1):21-30.
[25] Dayan F, Zulqarnain M, Hassan N. A ranking method for students of different socio economic backgrounds based on generalized fuzzy soft sets. Int J Sci Res (IJSR). 2017;6(9):2015-8.
[26] Dayan F, Zulqarnain M. On generalized interval valued fuzzy soft matrices. Am J Math Comp Modelling. 2018 Mar 30;3(1):1-9. doi: 10.11648/j.ajmcm.20180301.11
[27] Ye J. Multicriteria decision-making method based on a cosine similarity measure between trapezoidal fuzzy numbers. Int J Eng, Sci Technol. 2011;3(1). https://www.ajol.info/index.php/ijest/article/view/67654
[28] Pratiwi D, Lestari JP, Agushita D. Decision Support System to Majoring High School Student Using Simple Additive Weighting Method. Int J Comp Trends Technol. 2014 Apr;10(3):153-9.
[29] Wei G, Zhao X, Lin R, Wang H. Generalized triangular fuzzy correlated averaging operator and their application to multiple attribute decision making. App Math Modelling. 2012 Jul 1;36(7):2975-82. https://doi.org/10.1016/j.apm.2011.09.062
[30] Xu Z, Shang S, Qian W, Shu W. A method for fuzzy risk analysis based on the new similarity of trapezoidal fuzzy numbers. Expert Systems with Applications. 2010 Mar 15;37(3):1920-7. https://doi.org/10.1016/j.eswa.2009.07.015
[2] Hwang CL, Yoon K. Multiple attribute decision making: a state of the art survey. Lecture Notes in Eco Math Syst. 1981;186(1):1-15.
[3] Bellman RE, Zadeh LA. Decision-making in a fuzzy environment. Manag Sci. 1970 Dec;17(4):B-141. https://doi.org/10.1287/mnsc.17.4.B141
[4] Manokaran E, Subhashini S, Senthilvel S, Muruganandham R, Ravichandran K. Application of multi criteria decision making tools and validation with optimization technique-case study using TOPSIS, ANN & SAW. Int J Manag & Business Studies. 2011 Sep;1(3):112-5.
[5] Opricovic S, Tzeng GH. Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. Eur J Oper Res. 2004 Jul 16;156(2):445-55. https://doi.org/10.1016/S0377-2217(03)00020-1
[6] Jiang J, Chen YW, Tang DW, Chen YW. TOPSIS with belief structure for group belief multiple criteria decision making. Int J Auto Comp. 2010 Aug 1;7(3):359-64.
[7] Ling Z. (2006). Expected Value Method for Fuzzy Multiple Attribute Decision Making. Tsinghua Sci Technol. 11(1):102-106. 10.1016/S1007-0214(06)70161-4
[8] Beg I, Ashraf S. Similarity measures for fuzzy sets. Appl Comput. Math. 2009 Mar 1;8(2):192-202. https://www.researchgate.net/profile/Ismat_Beg/publication/228744370_Similarity_measures_for_fuzzy_sets/links/5835651208aef19cb8224581/Similarity-measures-for-fuzzy-sets.pdf
[9] Deni W, Sudana O, Sasmita A. Analysis and implementation fuzzy multi-attribute decision making SAW method for selection of high achieving students in faculty level. Int J Comp Sci Issues. 2013;10(1):674. https://search.proquest.com/openview/c94386bca63c77f1311000dbefa853ae/1?cbl=55228&pq-origsite=gscholar
[10] Sagar MK, Jayaswal P, Kushwah K. Exploring fuzzy SAW method for maintenance strategy selection problem of material handling equipment. Int J Current Eng Technol. 2013 Jun;3(2):600-5.
[11] Biswas P, Pramanik S, Giri BC. Cosine similarity measure based multi-attribute decision-making with trapezoidal fuzzy neutrosophic numbers. Neutrosophic Sets and Systems. 2015 Apr 1;8:46-56.
[12] Keeney RL, Raiffa H, Rajala DW. Decisions with multiple objectives: Preferences and value trade-offs. IEEE Trans Cybern. 1979 Jul;9(7):403-. https://ieeexplore.ieee.org/document/4310245
[13] Podvezko V. The comparative analysis of MCDA methods SAW and COPRAS. Eng Eco. 2011 Apr 7;22(2):134-46. https://journals.umt.edu.pk/index.php/SIR/Guidelines-for-Authors
[14] Feng CM, Wang RT. Performance evaluation for airlines including the consideration of financial ratios. J Air Trans Manag. 2000 Jul 1;6(3):133-42. https://doi.org/10.1016/S0969-6997(00)00003-X
[15] Zhang L, Xu X, Tao L. Some similarity measures for triangular fuzzy number and their applications in multiple criteria group decision-making. J App Math. 2013 Jan 1;2013. https://doi.org/10.1155/2013/538261
[16] Thor J, Ding SH, Kamaruddin S. Comparison of multi criteria decision making methods from the maintenance alternative selection perspective. Int J Eng Sci. 2013 Jul;2(6):27-34.
[17] Saeed M. An Application of Interval Valued Fuzzy Soft Matrix (Ivfsm) In Decision Making. Sci Int. 2016 Jun 30;28(3):2261-.
[18] Zulqarnain M. Comparative study of fuzzy soft matrix (FSM) and interval valued fuzzy soft matrix (IVFSM) in Decision making (Doctoral dissertation, University of Management and Technology Lahore).
[19] Zulqarnain M, Saeed M. A new decision making method on interval valued fuzzy soft matrix (IVFSM). J Advances in Math Comp Sci. 2017 Feb 25:1-7.
[20] Zulqarnain M, Dayan F, Saeed M. TOPSIS analysis for the prediction of diabetes based on general characteristics of humans. Int J Pharm Sci Res. 2018 Jul 1;9(7):2932-9.
[21] Zulqarnain RM, Xin XL, Saeed M, Ahmed N. Application of Interval Valued Fuzzy Soft Max-Min Decision Making Method in Medical Diagnosis. Int J Pharma Sci Rev Res. 2020;62(1):56-60.
[22] Zulqarnain RM, Xin XL, Saeed M, Ahmed N. Recruitment of Medical Staff in Health Department by Using TOPSIS Method. Int J Pharma Sci Rev Res. 2020;62(1):1-7.
[23] Zulqarnain M, Dayan F. Selection of best alternative for an automotive company by intuitionistic fuzzy TOPSIS method. Int J Sci Technol Res. 2017 Oct;6(10).
[24] Saeed M, Ali U, Ali J, Dayan F. Fuzzy Soft Relative Method and its Application in Decision Making Problem. Proceedings of the Pakistan Academy of Sciences: A. Physical and Computational Sciences. 2020 Oct 12;57(1):21-30.
[25] Dayan F, Zulqarnain M, Hassan N. A ranking method for students of different socio economic backgrounds based on generalized fuzzy soft sets. Int J Sci Res (IJSR). 2017;6(9):2015-8.
[26] Dayan F, Zulqarnain M. On generalized interval valued fuzzy soft matrices. Am J Math Comp Modelling. 2018 Mar 30;3(1):1-9. doi: 10.11648/j.ajmcm.20180301.11
[27] Ye J. Multicriteria decision-making method based on a cosine similarity measure between trapezoidal fuzzy numbers. Int J Eng, Sci Technol. 2011;3(1). https://www.ajol.info/index.php/ijest/article/view/67654
[28] Pratiwi D, Lestari JP, Agushita D. Decision Support System to Majoring High School Student Using Simple Additive Weighting Method. Int J Comp Trends Technol. 2014 Apr;10(3):153-9.
[29] Wei G, Zhao X, Lin R, Wang H. Generalized triangular fuzzy correlated averaging operator and their application to multiple attribute decision making. App Math Modelling. 2012 Jul 1;36(7):2975-82. https://doi.org/10.1016/j.apm.2011.09.062
[30] Xu Z, Shang S, Qian W, Shu W. A method for fuzzy risk analysis based on the new similarity of trapezoidal fuzzy numbers. Expert Systems with Applications. 2010 Mar 15;37(3):1920-7. https://doi.org/10.1016/j.eswa.2009.07.015
Published
2020-06-09
How to Cite
1.
Saeed M, Dayan F, Ali U. A Comparative Study of FCSM, FSAW and TOPSIS Techniques using Triangular Fuzzy Numbers. Sci Inquiry Rev. [Internet]. 2020Jun.9 [cited 2024Nov.27];4(2):17-0. Available from: https://journals.umt.edu.pk/index.php/SIR/article/view/1235
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