[1] Y. Akao, Development History of Quality Function Deployment, Minato, Tokyo 107 Japan,
1994.
[2] K. AlFalahi, Y. Atif and A. Abraham, Models of Influence in Online Social Networks, International
Journal of Intelligent Systems,29(2) (2014), 1-23.
[3] J.J. An, D. F. Li and J. X. Nan, A mean-area ranking based non-linear programming approach
to solve intuitionistic fuzzy bi-matrix games, Journal of Intelligent and Fuzzy Systems. 33(1)
(2017), 563-573.
[4] B. Ashtiani, F. Haghighirad, A. Makui and G. A. Montazer, Extension of fuzzy TOPSIS
method based on interval-valued fuzzy sets, Applied Soft Computing. 9(2) (2009), 457-461.
[5] K. T. Atanassov, On Intuitionistic Fuzzy Sets Theory, Berlin, Heidelberg, 2012.
[6] K. T. Atanassov,Intuitionistic fuzzy sets, Fuzzy Sets and Systems. 20(1) (1986), 87-96.
[7] C. H. Bahl and G. R. Hunt, Decision-making theory and DSS design, Newsletter ACM
SIGMIS: the Database for Advances in Information Systems, 15(4) (1984) 10-14.
[8] I. Beg and T. Rashid, TOPSIS for Hesitant Fuzzy Linguistic Term Sets, International Journal
of Intelligent System, 28(12) (2013), 1-10.
[9] F. E. Boran, S. Genc, M. Kurt and D. Akay, A multi-criteria intuitionistic fuzzy group deci-
sion making for supplier selection with TOPSIS method, Expert Systems with Applications,
36(8) (2009), 11363-11368.
[10] W. K. M. Brauers and E. K. Zavadskas, The MOORA method and its application to pri-
vatization in a transition economy by A new method: the MOORA method, Control and
Cybernetics, 35(2) (2006), 445-469.
[11] P. W. Bridgman, Dimensional Analysis, Yale University Press, New Haven, 1931.
[12] E. Buckingham, On Physically Similar Systems: Illustrations of the Use of Dimensional
Equations, Physical Review, 4(4) (1914), 345-376.
[13] M. Braglia and R. Gabbrielli, Technical note Dimensional analysis for investment selection
in industrial robots, International Journal of Production Research, 38(18) (2000), 4843-4848.
[14] A. Charnes, W. W. Cooper and E. Rhodes, Measuring the efficiency of decision making
units, European Journal of Operational Research, 2(6) (1978), 429-444.
[15] Z. Chen, K. Chin, Y. Li and Y. Yang, Proportional hesitant fuzzy linguistic term set for
multiple criteria group decision making, Information Sciences, 357 (2016), 61-87.
[16] N. Chen and Z. Xu, Hesitant fuzzy ELECTRE II approach: A new way to handle multi-
criteria decision making problems, Information Sciences, 292 (2015), 175-197.
[17] S. M. Chen and J. M. Tan, Handling Multicriteria Fuzzy Decision-making Problems Based
on Vague Set Theory, Fuzzy Sets System, 67(2) (1994), 163172.
[18] M. Collan, M. Fedrizzi and P. Luukka, New Closeness Coefficients for Fuzzy Similarity
Based Fuzzy TOPSIS: An Approach Combining Fuzzy Entropy and Multidistance, Advances
in Fuzzy Systems, 2015(2015), 1{12.
[19] L. de Boer, E. Labro and P. Morlacchi, A review of methods supporting supplier selection,
European Journal of Purchasing and Supply Management, 7(2) (2001), 75-89.
[20] J. Dong, D. Y. Yang and S. P. Wan, Trapezoidal intuitionistic fuzzy prioritized aggrega-
tion operators and application to multi-attribute decision making, Iranian Journal of Fuzzy
Systems, 12(4) (2015), 1-32.
[21] M. Dursun and E. E. Karsak, A fuzzy MCDM approach for personnel selection, Expert
Systems with Applications, 37(6) (2010), 4324-4330.
[22] D. Dubois, The role of fuzzy sets in decision sciences: Old techniques and new directions,
Fuzzy Sets and Systems, 184(1) (2011), 3-28.
[23] B. Efe, An integrated fuzzy multi criteria group decision making approach for ERP system
selection, Applied Soft Computing Journal, 38 (2016), 106-117.
[24] J. Garca-Alcaraz, I. A. Alvarado and A. Maldonado-Macias, Seleccion de proveedores basada
en analisis dimensional, Contadura y Administracion, 58(3) (2013), 249-278.
[25] R. Ginevicius, A New Determining Method for the Criteria Weights in Multicriteria Evalu-
ation, International Journal of Information Technology and Decision Making, 10(6) (2011),
1067-1095.
[26] M. Goyal, D. Yadav and A. Tripathi, Intuitionistic Fuzzy Genetic Weighted Averaging Op-
erator and its Application for Multiple Attribute Decision Making in E-Learning, Indian
Journal of Science and Technology, 9(1) (2016), 1-15.
[27] K. Govindan, S. Rajendran, J. Sarkis and P. Murugesan, Multi criteria decision making
approaches for green supplier evaluation and selection: a literature review, Journal of Cleaner
Production, 98 (2013), 66-83.
[28] K. Guo and W. Li, An attitudinal-based method for constructing intuitionistic fuzzy infor-
mation in hybrid MADM under uncertainty, Information Sciences, 208 (2012), 28-38.
[29] S. S. Hashemi, S. H. R. Hajiagha, E. K. Zavadskas and H. A. Mahdiraji, Multicriteria group
decision making with ELECTRE III method based on interval-valued eintuitionistic fuzzy
information, Applied Mathematical Modelling, 40 (2015), 1554-1564.
[30] J. Holland, Adaptation in natural and artificial systems, University of Michigan Press, Cambridge,
MA, 1975.
[31] D. H. Hong and C. H. Choi, Multicriteria fuzzy decision-making problems based on vague set
theory, Fuzzy Sets and Systems, 114(1) (2000), 103-113.
[32] C. Hwang and K. Yoon, Multiple Attribute Decision Making: Methods and Applications,
Springer-Verlag, New York, 1981.
[33] S. Khaleie and M. Fasanghari, An intuitionistic fuzzy group decision making method using
entropy and association coefficient, Soft Computing, 16(7) (2012), 1197-1211.
[34] D. Li, Notes on "Possibilistic programming approach for fuzzy multidimensional analysis of
preference in group decision making", Computers and Industrial Engineering, 73 (2014), 1-4.
[35] D. F. Li, Closeness coefficient based nonlinear programming method for interval-valued intu-
itionistic fuzzy multiattribute decision making with incomplete preference information, Applied
Soft Computing, 11(4) (2011), 3402-3418.
[36] D. F. Li, Decision and Game Theory in Management with Intuitionistic Fuzzy Sets, Springer
Heidelberg, Germany 2014.
[37] H. Liao, Z. Xu, X. J. Zeng and D. L. Xu, An enhanced consensus reaching process in group de-
cision making with intuitionistic fuzzy preference relations, Information Sciences, 329 (2016),
274-286.
[38] P. Liu and Y. Wang, Multiple attribute group decision making methods based on intuitionistic
linguistic power generalized aggregation operators, Applied Soft Computing, 17 (2014), 90-
104.
[39] F. R. Lima Junior, L. Osiro and L. C. R. Carpinetti, A comparison between Fuzzy AHP and
Fuzzy TOPSIS methods to supplier selection, Applied Soft Computing, 21 (2014), 194-209
[40] L. Z. Lin and H. R. Yeh, A perceptual measure of mobile advertising using fuzzy linguistic
preference relation, Iranian Journal of Fuzzy Systems, 10(5) (2013), 25-46.
[41] I. Mahdavi, N. Mahdavi-Amiri, A. Heidarzade and R. Nourifar, Designing a model of
fuzzy TOPSIS in multiple criteria decision making, Applied Mathematics and Computation,
206(2) (2008), 607-617.
[42] A. Mardani, A. Jusoh and E. K. Zavadskas, Fuzzy multiple criteria decision-making tech-
niques and applications Two decades review from 1994 to 2014, Expert Systems with Applications,
42(8) (2015), 4126-4148.
[43] A. Mardani, A. Jusoh, K. MD Nor, Z. Khalifah, N. Zakwan and A. Valipour, Multiple criteria
decision-making techniques and their applications a review of the literature from 2000 to
2014, Economic Research-Ekonomska Istraivanja, 28(1) (2015), 516-571.
[44] K. Maniya and M. G. Bhatt, A selection of material using a novel type decision-making
method: Preference selection index method, Materials and Design, 31(4) (2010), 1785-1789.
[45] F. Meng, and X. Chen, The symmetrical interval intuitionistic uncertain linguistic operators
and their application to decision making, Computers and Industrial Engineering, 98 (2016),
531-542.
[46] V. Mohagheghi, S. M. Mousavi and B. Vahdani, A new multi-objective optimization approach
for sustainable project portfolio selection: a real- world application under interval-valued
fuzzy environment, Iranian Journal of Fuzzy Systems, 13(6) (2016), 41-68.
[47] J. Nan, T.Wang and J. An, Intuitionistic Fuzzy Distance- Based Intuitionistic Fuzzy TOPSIS
Method and Application to MADM, International Journal of Fuzzy System Applications, 5(4)
(2016), 43-56.
[48] S. Opricovic and G. H. Tzeng, Compromise solution by MCDM methods: A comparative
analysis of VIKOR and TOPSIS, European Journal of Operational Research, 156(2) (2004),
445-455.
[49] Z. Pei, Intuitionistic fuzzy variables: Concepts and applications in decision making, Expert
Systems with Applications, 42(22) (2015), 9033-9045.
[50] B. Roy, Classement et choix en presence de points de vue multiples(la method ELECTRE),
Revue Francaise de Recherche Operationnelle, 2(1) (1968), 57-75.
[51] B. D. Rouyendegh (Babek Erdebilli) and T. E. Saputro, Supplier Selection Using Integrated
Fuzzy TOPSIS and MCGP: A Case Study, Procedia - Social and Behavioral Sciences, 116
(2014), 3957-3970.
[52] T.L. Saaty, The Analytic Hierarchy Process, McGraw-Hill, New Haven, 1980.
[53] T. L. Saaty, The Analytic Network Process: Decision Making with Dependence and Feedback,
RWS Publications, Pittsburgh, 1996.
[54] G. D. Saari and K. K. Sieberg, Are partwise comparisons reliable?, Research in Engineering
Design, 15(1) (2004), 62-71.
[55] C. Spearman, The proof and measurement of association between two things, The American
Journal of Psychology, 15(1) (1904), 72-101.
[56] F. Tatari and M. Mazouchi, A self-organized multi agent decision making system based on
fuzzy probabilities: the case of aphasia diagnosis, Iranian Journal of Fuzzy Systems, 11(6)
(2014), 21-46.
[57] A. Vega, J. Aguarn, J. Garca-Alcaraz and J. M. Moreno-Jimenez, Notes on Dependent
Attributes in TOPSIS, Procedia Computer Science, 31 (2014), 308-317.
[58] P. R. Villanueva and A. L. J. Garca, Evaluacion de Tecnologa utilizando TOPSIS en Pres-
encia de Multi-colinealidad en Atributos: Por qu usar distancia de Mahalanobis? Evaluation
of Technology using TOPSIS in Presence of Multi-collinearity in Attributes: Why use the
Mahalanobis distance, Revista de La Facultad de Ing. Univ. Antioquia, (67) (2013), 31-42.
[59] H. Wang and Z. Xu, Interactive algorithms for improving incomplete linguistic preference
relations based on consistency measures, Applied Soft Computing, 42 (2016), 66-79.
[60] F. Wang, S. and Zeng and C. Zhang, A method based on Intuitionistic fuzzy dependent ag-
gregation operators for supplier selection, Mathematical Problems Engineering, 2013 (2013),
1-9.
[61] T. C.Wang and Y. H. Chen, Applying fuzzy linguistic preference relations to the improvement
of consistency of fuzzy AHP, Information Sciences, 178 (2008), 3755-3765.
[62] S. P. Wan and Y. J. Zhu, Triangular intuitionistic fuzzy triple bonferroni harmonic mean
operators and application to multi-attribute group decision making, Iranian Journal of Fuzzy
Systems, 13(5) (2016). 117-145.
[63] T. Willis, C. Huston and F. Pohlkamp, Evaluation measures of justin- time supplier perfor-
mance, Production and Inventory Management Journal, 34(2) (1993), 1-6.
[64] D. A. Wood, Supplier selection for development of petroleum industry facilities , applying
multi-criteria decision making techniques including fuzzy and intuitionistic fuzzy TOPSIS
with flexible entropy weighting, Journal of Natural Gas Science and Engineering, 28 (2016),
594-612.
[65] Z. Xu, Intuitionistic Fuzzy Multiattribute Decision Making: An Interactive Method, IEEE
Transactions on Fuzzy Systems, 20(3) (2012), 514-525.
[66] Z. Xu, Intuitionistic Fuzzy Aggregation Operators, IEEE Transactions on Fuzzy Systems,
15(6) (2007), 1179-1187.
[67] Z. Xu, S. Member and H. Liao, Intuitionistic fuzzy analytic hierarchy process, Fuzzy Systems,
IEEE Transactions on. 22(4) (2014), 749-761.
[68] Z. Xu and R. R. Yager, Intuitionistic Fuzzy Bonferroni Means, International Journal of
Intelligent Systems, 27(2) (2011), 23-47.
[69] Z. Xu and R. R. Yager, Some geometric aggregation operators based on intuitionistic fuzzy
sets, International Journal of General Systems, 35(4) (2006), 417-433.
[70] Z. Yue, Group decision making with multi-attribute interval data, Information Fusion, 14(4)
(2013), 551-561.
[71] E. K. Zavadskas, J. Antucheviciene and Z. Turskis, Hybrid multiple-criteria decision-making
methods: A review of applications in engineering, Scientia Iranica, 23 (2016), 1-20.
[72] L. Zadeh, Fuzzy Sets, Information and Control, 8(3) (1965), 338-353.
[73] M. Zeydan, A combined methodology for supplier selection and performance evaluation, Expert
Systems with Applications, 38(3) (2011), 2741-2743.
[74] W. Zhou and J. He, Intuitionistic fuzzy normalized weighted Bonferroni mean and its ap-
plication in multicriteria decision making, Journal of Applied Mathematics, (2012) (2012),
1-22.