A new approach for evaluation of renewable energy resources: A case of Turkey

References

• Atanassov, K. T. 1986. Intuitionistic fuzzy sets. Fuzzy Sets and Systems 20 (1):87–96.
   Web of Science ®Google Scholar
• Balin, A., and H. Baraçli. 2015. A fuzzy multi-criteria decision making methodology based upon the interval Type-2 fuzzy sets for evaluating renewable energy alternatives in Turkey. Technological and Economic Development of Economy 23 (5):742–63.
   Web of Science ®Google Scholar
• Büyüközkan, G., and S. Güleryüz. 2016. An integrated DEMATEL-ANP approach for renewable energy resources selection in Turkey. International Journal of Production Economics 182:435–48.
   Web of Science ®Google Scholar
• Cayir Ervural, B., S. Zaim, O. F. Demirel, Z. Aydin, and D. Delen. 2018. An ANP and fuzzy TOPSIS-based SWOT analysis for Turkey’s energy planning. Renewable and Sustainable Energy Reviews 82 (2):1538–50.
   Google Scholar
• Çolak, M., and İ. Kaya. 2017. Prioritization of renewable energy alternatives by using an integrated fuzzy MCDM model: A real case application for Turkey. Renewable and Sustainable Energy Reviews 80:840–53.
   Web of Science ®Google Scholar
• Erdogan, M., and İ. Kaya. 2015. An integrated multi-criteria decision-making methodology based on type-2 fuzzy sets for selection among energy alternatives in Turkey. Iranian Journal of Fuzzy Systems 12 (1):1–25.
   Web of Science ®Google Scholar
• Ertay, T., C. Kahraman, and İ. Kaya. 2013. Evaluation of renewable energy alternatives using MACBETH and fuzzy AHP multicriteria methods: the case of Turkey. Technological and Economic Development of Economy 19 (1):38–62.
   Web of Science ®Google Scholar
• Intarapaiboon, P. 2016. A hierarchy-based similarity measure for intuitionistic fuzzy sets. Soft Computing 20 (5):1909–19.
   Web of Science ®Google Scholar
• Kahraman, C., and İ. Kaya. 2010. A fuzzy multicriteria methodology for selection among energy alternatives. Expert Systems with Applications 37 (9):6270–81.
   Web of Science ®Google Scholar
• Kaya, T., and C. Kahraman. 2010. Multicriteria renewable energy planning using an integrated fuzzy VIKOR & AHP methodology: the case of Istanbul. Energy 35 (6):2517–27.
   Web of Science ®Google Scholar
• Pak, B., Y. E. Albayrak, and Y. C. Erensal. 2015. Renewable energy perspective for Turkey using sustainability indicators. International Journal of Computational Intelligence Systems 8 (1):187–97.
   Web of Science ®Google Scholar
• Opricovic, S. 1998. Visekriterijumska Optimizacija Sistema U Gradevinarstvu. Belgrade: Faculty of Civil Engineering.
   Google Scholar
• Opricovic, S., and G.-H. Tzeng. 2004. Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research 156 (2):445–55.
   Web of Science ®Google Scholar
• Opricovic, S., and G.-H. Tzeng. 2007. Extended VIKOR method in comparison with outranking methods. European Journal of Operational Research 178 (2):514–29.
   Web of Science ®Google Scholar
• Ozgur, M. A. 2008. Review of Turkey’s renewable energy potential. Renewable Energy 33 (11):2345–56.
   Web of Science ®Google Scholar
• Özkale, C., C. Celik, A. C. Turkmen, and E. S. Cakmaz. 2017. Decision analysis application intended for selection of a power plant running on renewable energy sources. Renewable and Sustainable Energy Reviews 70:1011–21.
   Web of Science ®Google Scholar
• Park, J. H., H. J. Cho, J. S. Hwang, and Y. C. Kwun 2010. Extension of the VIKOR method to dynamic intuitionistic fuzzy multiple attribute decision making. Paper read at 3rd International Workshop on Advanced Computational Intelligence, IWACI 2010.
   Google Scholar
• Saaty, T. L. 1980. The Analytic Hierarchy Process, NY. McGraw-Hill, USA. Cook WD and Seiford LM. (1978). Priority Ranking and Consensus Formation, Management Science 24:1721–32.
   Google Scholar
• Şengül, Ü., M. Eren, S. Eslamian Shiraz, V. Gezder, and A. B. Şengül. 2015. Fuzzy TOPSIS method for ranking renewable energy supply systems in Turkey. Renewable Energy 75:617–25.
   Web of Science ®Google Scholar
• Shu, M. H., C. H. Cheng, and J. R. Chang. 2006. Using intuitionistic fuzzy sets for fault-tree analysis on printed circuit board assembly. Microelectronics Reliability 46 (12):2139–48.
   Web of Science ®Google Scholar
• Zadeh, L. A. 1965. Fuzzy sets. Information and Control 8 (3):338–53.
   Google Scholar