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Yahyaie, Leila, Khanmohammadi, Sohrab. (1395). A New Multi-Criteria Decision Making Based on Fuzzy- Topsis Theory. , 2(4), 39-48.
Leila Yahyaie; Sohrab Khanmohammadi. "A New Multi-Criteria Decision Making Based on Fuzzy- Topsis Theory". , 2, 4, 1395, 39-48.
Yahyaie, Leila, Khanmohammadi, Sohrab. (1395). 'A New Multi-Criteria Decision Making Based on Fuzzy- Topsis Theory', , 2(4), pp. 39-48.
Yahyaie, Leila, Khanmohammadi, Sohrab. A New Multi-Criteria Decision Making Based on Fuzzy- Topsis Theory. , 1395; 2(4): 39-48.

A New Multi-Criteria Decision Making Based on Fuzzy- Topsis Theory

Journal of Advances in Computer Engineering and Technology
مقاله 5، دوره 2، شماره 4 - شماره پیاپی 8، بهمن 2016، صفحه 39-48  XML اصل مقاله (475.19 K)
نوع مقاله: Original Research Paper
نویسندگان
Leila Yahyaie email 1؛ Sohrab Khanmohammadi2
1Department of Computer, Islamic Azad University, Salmas Branch, Salmas, Iran.
2Department of Computer Engineering, University of Tabriz,Tabriz, Iran.
چکیده
Abstract— In this paper, a new extended method of multi criteria decision making based on fuzzy-Topsis theory is introduced. fuzzy mcdm algorithm for determining the best choice among all possible choices when the data are fuzzy is also presented. Using a new index leads to procedure for choosing fuzzy ideal and negative ideal solutions directly from the fuzzy data observed alternatives.in this algorithm we used triangular fuzzy number. Mostly, it is not possible to gather precise data, so decision making based on these data loses its efficiency. The fuzzy theory has been used to overcome this draw back. In multi-criteria decision making, criteria can correlate with each other, most of which are ignored in classic MCDM. In this paper, correlation coefficient of fuzzy criteria has been studied to adapt the interrelation between criteria and a new algorithm is proposed to obtain decision making. Finally the efficiency of suggested method is demonstrated with an example..
کلیدواژه‌ها
MCDM؛ Correlation؛ fuzzy-Topsis
مراجع
[1] G. O. Young, “Synthetic structure of industrial plastics (Book style with paper title and editor),” in Plastics, 2nd ed. vol. 3, J. Peters, Ed. New York: McGraw-Hill, 1964, pp. 15–64.
[2] M.J. Asgharpour, Multi criteria decision making, fourth ed., Tehran University Press (In Farsi), 2004, pp. 456.
[3] J. Jiang , Yu-Wang Chen, Ying-wu Chen, Ke-wei Yang, TOPSIS with fuzzy belief structure for group belief multiple criteria decision making, Expert Systems with Applications 38 (2011) 9400–9406
[4] B. Vahdani, S. M. Mousavi, R. Tavakkoli-Moghaddam, Group decision making based on novel fuzzy modified TOPSIS method, Applied Mathematical Modeling. 35 (2011) 4257–4269,
[5] Timothy J.Ross , Fuzzy logic with engineering applications, second Ed. John Wiley & Sons Ltd, The Atrium, Southern Gate, Chic Hester, England , 2004
[6] M. Izadikhah, Using the Hamming distance to extend TOPSIS in a fuzzy environment, Journal of Computational and Applied Mathematics. 231 (2009) 200-207
[7] I. Mahdavi, N. Mahdavi-Amiri, A. Heidarzade,R.Nourifar, Designing a model of fuzzy TOPSIS in multiple criteria decision making, Applied Mathematics and Computation. 206 (2008) 607–617
[8] Y. M. Wang, T. M. S. Elhag, Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment, Expert Systems with Applications. 31 (2006) 309–319,
[9] J. F. Ding and C. C. Chou, A fuzzy MCDM model of service performance for container ports, Scientific research and Essays. 6 (2011) 559-556
[10] Ting-Yu Chen, Interval-valued fuzzy TOPSIS method with leniency reduction and an experimental analysis, Applied Soft Computing. 11 (2011) 4591–4606
[11] B.B. Chaudhuri and A. Bhattacharya, On correlation between two fuzzy sets, Fuzzy Sets and Systems. 118 (2001) 447-456,
[12] W. Hung, J. Wu, Correlation of intuitionistic fuzzy sets by centroid method, Information Sciences. 144 (2002) 219–225
[13] M. Yurdakul, Y. Tansel İÇ. Application of correlation test to criteria selection for multi criteria decision making (MCDM), models.Int J AdvManufTechnol. 40( 2009) 403–412
[14] T. C. Wang, H. D. Lee, Developing A fuzzy TOPSIS approach based on subjective weights and objective weights, Expert Systems with Applications. 36 (2009) 8980–8985
[15] W. Pedrycz, F. Gomide , An introduction to fuzzy sets analysis and design, Prentice’ Hall of India ,2004
[16] V. S. Vaidyanathan, Correlation of Triangular Fuzzy Variables Using Credibility Theory. International journal of computational cognition. HTTP://WWW.IJCC.US, 8 (2010)
[17] F. HosseinzadehLotfi, T. Allahviranloo, M. AlimardaniJondabeh, A New Method for Complex Decision Making Based on TOPSIS for Complex Decision Making Problems with Fuzzy Data, Applied Mathematical Sciences. 1 (2007) 2981-2987
[18] Z. Yue, An extended TOPSIS for determining weights of decision makers with interval numbers, Knowledge-Based Systems 24 (2011) 146–153
[19] C. H. Yeh, Y. H. Chang, Modeling subjective evaluation for fuzzy group multicriteria decision making, European Journal of Operational Research. 194 (2009) 464–473
[20] N. Mahdavi-Amiri, S. H. Nasseri, A. Yazdani, Fuzzy primal simplex algorithm for solving fuzzy linear programming problem, Iranian Journal of Operation Researcher (IJOR). 1 (2009) 68-84.
F. Liguo, L. Yanhong, A New MCDM Method in Transmission Network Planning Based on Gray Correlation Degree and TOPSIS, in: Proceedings of the 27th Chinese Control Conference, Kunming,Yunnan, China, 2008, pp.462-467

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