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• [1] Karakaşoğlu, N. (2008). Bulanık çok kriterli karar verme yöntemleri ve bir uygulama, Yüksek Lisans Tezi, Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü, Denizli.
• [2] Chen, C.T. ve Sue-Fen Huang, S.F. (2006). Order-Fullfillment Availabelity Analysis İn The Supply Chain System With Fuzzy Operation Times, International Journal of Production Economics, 101, ss.185-193.
• [3] Türk, S., John, R., & Özcan, E. (2014, September). Interval type-2 fuzzy sets in supplier selection. In Computational Intelligence (UKCI), 2014 14th UK Workshop on (pp. 1-7). IEEE.
• [4] Wu, Z. ve Chen, Y. (2007). The maximizing deviation method for group multiple attribute decision making under linguistic environment. Fuzzy Sets Syst., 158(14):1608–1617, July 2007.
• [5] Eminov M., Ballı S. (2004). Karmaşık Problemler İçin Belirsizlik Altında Çok Kriterli Bulanık Karar Verme, Yöneylem Araştırması ve Endüstri Mühendisliği XXIV. Ulusal Kongresi Bildiriler Kitabı, Gaziantep-Adana, s. 440-443.
• [6] Pala, O. (2013). Bulanık mantık ve çok kriterli karar verme uygulaması, Yüksek Lisans Tezi, Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü, İzmir.
• [7] Paksoy, T. (2013). Bulanık Küme Teorisi. Nobel Yayınevi, Ankara.
• [8] Ulu, C., (2013). Granüler tip-2 bulanık yapılar kullanılarak sistemlerin modellenmesi ve kontrolü, Doktora Tezi, İstanbul Teknik Üniversitesi Fen Bilimleri Enstitüsü, İstanbul.
• [9] Thomas, D. J. & Griffin, P. M. (1996). Coordinated supply chain management. European journal of operational research, 94(1), 1-15.
• [10] Şen, Z. (2004). Fuzzy logic and system models in water sciences. Turkish Water.
• [11] Zadeh L. A. (1975). The concept of a linguistic variable and its application to approximate reasoning-1, Inform. Sci., 8, pp. 199–249.
• [12] Karnik N. N. (1998). Type-2 fuzzy logic systems. Ph.D. Dissertation, ProQuest Dissertations & Theses (PQDT).
• [13] Castillo O., Melin P. (2008). Type-2 Fuzzy Logic: Theory and Applications. Verlag Berlin Heidelberg, Springer. [14] Mendel J. M. (2001). Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions. Upper Saddle River, NJ, Prentice-Hall.
• [15] Bulut, M. (2010). Bulanık mantık için yeni bir yaklaşım: tip-2 bulanık mantık. e-Journal of New World Sciences Academy 5 (3),ISSN:1306-3111, pp.541-557.
• [16] Linda O., Manic M. (2011). Interval type-2 fuzzy voter design for fault tolerant systems. Information Sciences, 181 (14), pp. 2933–2950.
• [17] Jammeh E. A., Fleury M., Wagner C., Hagras H., Ghanbari M. (2009). Interval type-2 fuzzy logic congestion control for video streaming across IP networks. IEEE Transactions on Fuzzy Systems, 17 (5), pp.1123–1142.
• [18] Kahraman, C., Büyüközkan, G. ve Ruan, D. (2004). A Fuzzy Multi-Criteria Decision Approach for Software Development Strategy Selection, International Journal of General Systems, 33 (2–3), p.259 280.
• [19] Ayağ, Z. Ve Özdemir, R.G. (2006). A Fuzzy AHP Approach to Evaluating Machine Tool Alternatives, Journal of Intelligent Manufacturing, 17, p.179-190.
• [20] Ferdinando, D. M. ve Salvatore, S. (2014). Type-2 interval fuzzy rule-based systems in spatial analysis. Information Sciences 279, ss. 199-212.
• [21] Qin, J., Liu, X. ve Pedrycz, W. (2016). An extended TODIM multi-criteria group decision making method for green supplier selection in interval type-2 fuzzy environment. Pll: S03772217(16)30811 6, DOI: 10.1016/j.ejor.2016.09.059.
• [22] Keshavarz, M., Zavadskas, E. K. ve Amiri, M. (2016). Multi-criteria evaluation of green suppliers using an extended WASPAS method with interval type-2 fuzzy sets. Journal of Cleaner Production, pp. 213-229.
• [23] Heidarzade, A., Mahdavi, I. ve Amiri, N. M. (2016). Supplier selection using a clustering method based on a new distancefor interval type-2 fuzzy sets: A case study. Applied Soft Computing, pp. 213-231.
• [24] Yaakob, A., Khalif, K., Naim, KM., Gegov, A. E., Rahman, A. And Fatimah, S. (2015). Interval type 2- fuzzy rule based system approach for selection of alternatives using TOPSIS. In: Proceedings of the 7th international joint conference on computational intelligence: SCITEPRESS – Science and Technology Publications, pp. 112-120. ISBN 978-989-758-157-1.
• [25] Liao, H., Xu, Z., & Zeng, X. J. (2015). Hesitant fuzzy linguistic VIKOR method and its application in qualitative multiple criteria decision making. IEEE Transactions on Fuzzy Systems, 23(5), 1343-1355.
• [26] Chan, F. T. S., Kumar, N. (2007). Global Supplier Development Considering Risk Factors Using Fuzzy Extended AHP-based Approach, Omega International Journal of Management Science, 35, p.417-431.