
تعداد نشریات | 32 |
تعداد شمارهها | 757 |
تعداد مقالات | 7,326 |
تعداد مشاهده مقاله | 12,142,309 |
تعداد دریافت فایل اصل مقاله | 8,292,010 |
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 | ||
مقاله 2، دوره 12، شماره 1، اردیبهشت 2015، صفحه 1-25 اصل مقاله (1.96 M) | ||
نوع مقاله: Research Paper | ||
شناسه دیجیتال (DOI): 10.22111/ijfs.2015.1839 | ||
نویسندگان | ||
Melike Erdogan* ؛ ihsan Kaya | ||
Department of Industrial Engineering, Yildiz Technical University, Yildiz, BESIKTAS, Istanbul, Turkey | ||
چکیده | ||
Energy is a critical factor to obtain a sustainable development for countries and governments. Selection of the most appropriate energy alternative is a completely critical and a complex decision making problem. In this paper, an integrated multi-criteria decision-making (MCDM) methodology based on type-2 fuzzy sets is proposed for selection among energy alternatives. Then a roadmap has been created for Turkey. To overcome uncertainties in decision making process, the fuzzy set theory (FST) is suggested. For this aim, two of the most known MCDM methodologies are reconsidered by using type-2 fuzzy sets. Fuzzy Analytic Hierarchy Process (FAHP) based on interval type-2 fuzzy sets is constructed and is used to obtain the weights of the criteria affecting energy alternatives. To rank the energy alternatives, the other MCDM method that is Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is fuzzified by interval type-2 fuzzy sets. The proposed integrated MCDM methodology based on interval type-2 fuzzy sets is applied to obtain a road map of energy policies for Turkey. | ||
کلیدواژهها | ||
Energy؛ Multi criteria decision making؛ Interval type-2 fuzzy sets؛ AHP؛ TOPSIS | ||
مراجع | ||
[1] A. J. Ansari and I. Ashraf, Best energy option selection using fuzzy multi-criteria decision making approach, International Journal of Advanced Renewable Energy Research, 1 (2012), 269-275. [2] L. Balezentiene, D. Streimikiene and T. Balezentis, Fuzzy decision support methodology for sustainable energy crop selection, Renewable and Sustainable Energy Reviews., 17 (2013), 83{93. [3] M. Beccali, M. Cellura and D. Ardent, Decision making in energy planning: The electre multi criteria analysis approach compared to a fuzzy-sets methodology, Energy Conversion and Management, 39 (1998), 16-18. [4] H. Benli, Potential of renewable energy in electrical energy production and sustainable energy development of turkey: Performance and policies, Renewable Energy, 50 (2013), 33-46. [5] M. Bernasconi, C. Choirat and R. Seri, Empirical properties of group preference aggregation methods employed in AHP: Theory and evidence, European Journal of Operational Research., 232 (2014), 584{592. [6] J. J. Buckley, Fuzzy hierarchical analysis, Fuzzy Sets And Systems, 17 (1985), 233-247. [7] F. Cavallaro, Fuzzy TOPSIS approach for assessing thermal-energy storage in concentrated solar power (CSP) systems, Applied Energy, 87 (2010), 496{503. [8] P. L. Chang, C. W. Hsu and C. Y. Lin, Assessment of hydrogen fuel cell applications using fuzzy multiple-criteria decision making method, Applied Energy, 100 (2012), 93-99. [9] H. H. Chen and C. Pang, Organizational forms for knowledge management in photovoltaic solar energy industry, Knowledge-Based Systems, 23 (2010), 924{933. [10] S. M. Chen and L. W. Lee, Fuzzy multiple attributes group decision-making based on the interval type-2 TOPSIS method, Expert Systems with Applications, 37 (2010), 2790{2798. [11] D. Choudhary and R. Shankar, An STEEP-fuzzy AHP-TOPSIS framework for evaluation and selection of thermal power plant location: A case study from India, Energy, 42 (2012), 510-521. [12] T. U. Daim, X. Li, J. Kim and S. Simms, Evaluation of energy storage technologies for integration with renewable electricity: Quantifying expert opinions, Environmental Innovation and Societal Transitions, 3 (2012), 29-49. [13] M. S. Garca-Cascales, M. T. Lamata and J. M. Sanchez-Lozano, Evaluation of photovoltaic cells in a multi-criteria decision making process, Annals of Operations Research, 199 (2012), 373{391. [14] L. A. Greening and S. Bernow, Design of coordinated energy and environmental policies: Use of multi-criteria decision-making, Energy Policy, 32 (2004), 721{735. [15] E. Hisdal, The IF THEN ELSE statement and interval-valued fuzzy sets of higher type, International Journal of Man-Machine Studies, 15 (1981), 385{455. [16] S. Hsueh, A fuzzy utility-based multi-criteria model for evaluating Households' energy conservation performance: A taiwanese case study, Energies., 5 (2012), 2818-2834. [17] C. L. Hwang and K. S. Yoon, Multiple attribute decision making: Methods and applications, Springer-Verlag, Berlin, 1981. [18] Y. Jing, H. Bai and J.Wang, A fuzzy multi-criteria decision-making model for CCHP systems driven by dierent energy sources, Energy Policy, 42 (2012), 286-296. [19] R. I. John, Type 2 fuzzy sets: An appraisal of theory and applications, International Journal of Uncertainty, Fuzziness Knowledge-Based Systems, 6 (1998), 563{576. [20] C. Kahraman, _I. Kaya and S. Cebi, A comparative analysis for multi attribute selection among renewable energy alternatives using fuzzy axiomatic design and fuzzy analytic hierarchy process, Energy, 34 (2009), 1603-1616. [21] C. Kahraman, and _I. Kaya, A fuzzy multicriteria methodology for selection among energy alternatives, Expert System with Applications, 37 (2010), 6270-6281. [22] C. Kahraman, C. Seluk and _I. Kaya, Selection among renewable energy alternatives using fuzzy axiomatic design: The case of Turkey, Journal of Universal Computer Science, 16 (2010) , 82-102. [23] C. Kahraman, B. Oztayi, I. U. Sar{ and E. Turanoglu, Fuzzy analytic hierarchy process with interval type-2 fuzzy sets, Knowledge-Based Systems, 59 (2014), 48-57. [24] H. Y. Kang, M. C. Hung, W. L. Pearn, A. H. I. Lee and M. S. Kang, An integrated multicriteria decision making model for evaluating wind farm performance, Energies., 4 (2011), 2002-2026. [25] N. N. Karnik and J. M. Mendel, Operations on type-2 fuzzy sets, Fuzzy Sets and Systems, 122 (2001), 327{348. [26] T. Kaya and C. Kahraman, Multicriteria decision making in energy planning using a modi ed fuzzy TOPSIS methodology, Expert Systems with Applications, 38 (2011), 6577{6585. [27] G. Koaslan, Turkiye'nin Enerji Kaynaklar{ ve Alternatif Bir Kaynak Olarak Ruzgar Enerjisinin Degerlendirilmesi. Istanbul University, Institute of Social Sciences, Master's Thesis, Istanbul (in Turkish), 2006. [28] A. H. I. Lee, H. H. Chen and H. Y. Kang, A model to analyze strategic products for photovoltaic silicon thin-lm solar cell power industry, Renewable and Sustainable Energy Reviews, 15 (2011), 1271{1283. [29] A. H. I. Lee, M. C. Hung, H. Y. Kang and W. L. Pearn, A wind turbine evaluation model under a multi-criteria decision making environment, Energy Conversion and Management, 64 (2012), 289-300. [30] G. Lee, K. S. Jun and E. S. Cheng, Robust spatial ood vulnerability assessment for Han River using fuzzy TOPSIS with -cut level set, Expert Systems with Applications, 41 (2014), 644{654. [31] L. W. Lee and S. M. Chen, Fuzzy multiple attributes group decision-making based on the extension of topsis method and interval type-2 fuzzy sets, Proceedings of the Seventh International Conference on Machine Learning and Cybernetics, IEEE, Kunming, (2008), 3260-3265. [32] S. K. Lee, G. Mogi, S. K. Lee and J. W. Kim, Prioritizing the weights of hydrogen energy technologies in the sector of the hydrogen economy by using a fuzzy AHP approach, International Journal of Hydrogen Energy, 36 (2011), 1897-1902. [33] S. K. Lee, G. Mogi, S. K. Lee, K. S. Hui and J. W. Kim , Econometric analysis of the R&D performance in the national hydrogen energy technology development for measuring relative eciency: The fuzzy AHP/DEA, International Journal of Hydrogen Energy, 35 (2010), 2236- 2246. [34] A. Manzardo, J. Ren, A. Mazzi and A. Scipioni, A grey-based group decision-making methodology for the selection of hydrogen technologies in life cycle sustainability perspective, International Journal of Hydrogen Energy, 37 (2012), 17663{17670. [35] J. M., Mendel, Advances in type-2 fuzzy sets and systems, Information Sciences, 177 (2007), 84{110. [36] J. M. Mendel, Type-2 fuzzy sets: Some questions and answers, IEEE Neural Networks Society, (2003), 10-13. [37] J. M. Mendel, R. I.John and F. L. Liu, Interval type-2 fuzzy logical systems made simple, IEEE Transactions on Fuzzy Systems., 14 (2006), 808{821. [38] O. O. Mengi and I. H. Altas, A fuzzy decision making energy management system for a PV/Wind renewable energy system, Innovations in Intelligent Systems and Applications (INISTA), 2011 International Symposium on, Istanbul , 436{440, (2011). [39] A. Phdungsilp , Integrated energy and carbon modeling with a decision support system: Policy scenarios for low-carbon city development in Bangkok, Energy Policy, 38 (2010), 4808{4817. [40] J. Rezaei, R. Ortt and V. Scholten, An improved fuzzy preference programming to evaluate entrepreneurship orientation, Applied Soft Computing, 13 (2013), 2749{2758. [41] D. Ruan, J. Lu, E. Laes, G. Zhang, J. Ma and G. Meskens, Multi-criteria group decision support with linguistic variables in long-term scenarios for belgian energy policy, Journal of Universal Computer Science, 16 (2010), 103-120. [42] T. L. Saaty, A scaling method for priorities in hierarchical structures, Journal of Mathematical Psychology, 15(3) (1977), 234{281. [43] T. L. Saaty, The Analytic Hierarchy Process, McGraw-Hill, New York, 1980. [44] A. Sadeghi, T. Larimian and A. Molabashi, Evaluation of renewable energy sources for generating electricity in province of Yazd: A fuzzy MCDM approach, Procedia - Social and Behavioral Sciences, 62 (2012), 1095{1099. [45] A. Satman, Turkiye'nin Enerji Vizyonu, TESKON2007, Izmir, (in Turkish), 2007. [46] Y. C Shen, G. T. R. Lin, K. P. Li and B. J. C. Yuan, An assessment of exploiting renewable energy sources with concerns of policy and technology, Energy Plicy., 38 (2010), 4604{4616. [47] M. Q. Suo, Y. P. Li and G. H. Huang, Multi criteria decision making under uncertainty: An advanced ordered weighted averaging operator for planning electric power systems, Engineering Applications of Articial Intelligence, 25 (2012), 72-81. [48] E. Toklu, Overview of potential and utilization of renewable energy sources in ,Turkey Renewable Energy, 50 (2013), 456-463. [49] Turkish Republic Ministry of Energy and Natural Resources, http://www.enerji.gov.tr/, 12.02.2013. [50] UCTEA Chamber of Mechanical Engineers Report, April 2012. [51] UCTEA Chamber of Electrical Engineers, Electricity Privatization Report, March 2012. [52] P. J. M. Van Laarhoven and W. Pedrycz, A fuzzy extension of Saaty's priority theory, Fuzzy Sets and Systems, 11 (1983), 229-241. [53] L. Wang, L. Xu and H. Song, Environmental performance evaluation of Beijing's energy use planning, Energy Policy., 39 (2011), 3483-3495. [54] Y. Yazar, Turkiye'nin Enerjideki Durumu ve Geleceui. SETA, Foundation for Political Economic and Social Research., www.setav.org, (in Turkish), December (2010). [55] L. A. Zadeh, Fuzzy set, Information and Control, 8 (1965), 338{353. [56] L. A. Zadeh, The concept of a linguistic variable and its application to approximate reasoning { 1, Information Science, 8 (1975), 199{249. [57] T. Zgun , Bulan{k Analitik Hiyerari Prosesi, Yildiz Technical University, Institute of Science, Master's Thesis, Istanbul (in Turkish), 2006. | ||
آمار تعداد مشاهده مقاله: 3,914 تعداد دریافت فایل اصل مقاله: 3,969 |