A DECISION PROCEDURE FOR SUSTAINABLE ENERGY MANAGEMENT AND PLANNING BASED ON MULTI CRITERIA DECISION MAKING UNDER INTUITIONISTIC FUZZY ENVIRONMENT

Year 2019, Volume: 17 Issue: 2, 21 - 41, 30.06.2019

Şebnem Yılmaz Balaman , Sedef Çalı

https://doi.org/10.11611/yead.463223

Abstract

This study aims to rank alternative sustainable energy systems and to present
the most convenient one utilizing a MCDM methodology based on integration of
intuitionistic fuzzy ELECTRE and VIKOR methods. Four experts on sustainable
energy have assessed the alternative energy systems, namely biomass, solar and
wind energy systems according to sustainability criteria, which are divided
into 4 main categories, namely environmental, social, economic and technical.
In this scope, 16 sub-criteria are determined and the values of these
sub-criteria are determined by the experts using linguistic variables expressed
by intuitionistic fuzzy numbers. The weights of decision makers and criteria
with significant contribution on the ranking procedure are specified via
Entropy method. The methodology reveals that Solar Energy is the most
convenient energy system for Turkey, whereas the ranks of wind and biomass
systems change according to different decision making strategies.

Keywords

ELECTRE, VIKOR, Intuitionistic Fuzzy Sets, Renewable Energy

Supporting Institution

Dokuz Eylül University Scientific Research Coordination Unit

Project Number

2017.KB.FEN.026

SÜRDÜRÜLEBİLİR ENERJİ YÖNETİMİ VE PLANLAMASI İÇİN SEZGİSEL BULANIK ÇEVREDE ÇOK KRİTERLİ KARAR VERME YÖNTEMLERİNE DAYALI BİR KARAR PROSEDÜRÜ

Abstract

Bu çalışma, alternatif enerji sistemlerini
sezgisel bulanık ELECTRE ile VIKOR yöntemlerinin entegrasyonuna dayanan bir
yaklaşımı kullanarak sıralamayı ve aralarından en uygununu seçmeyi
amaçlamaktadır. Yenilenebilir enerji konusunda uzman dört karar verici,
yenilenebilir enerji sistemi alternatiflerinden biyokütle, güneş ve rüzgâr
enerji sistemlerini belirlenen ekonomik, çevresel, sosyal ve teknik
faktörlerden oluşan 4 ana kriter ve bu kapsamda toplam 16 alt kritere göre
sezgisel bulanık sayılarla ifade edilebilen dilsel değişkenler aracılığıyla
değerlendirmiştir. Alternatiflerin sıralanmasında büyük öneme sahip olan karar
verici ve kriter ağırlıkları, Entropi Metodu ile belirlenmiştir. Kullanılan
yaklaşım, uzman değerlendirmelerine göre Güneş Enerjisi sistemlerinin Türkiye
için en uygun enerji sistemi olduğunu ortaya çıkarmakta, Rüzgar ve Biyokütle
enerjilerinin sırası ise karar verme stratejisine göre değişmektedir.

Keywords

ELECTRE, VIKOR, Sezgisel Bulanık Kümeler, Yenilenebilir Enerji

Project Number

2017.KB.FEN.026

References

• Atanassov, K. T. (1986) “Intuitionistic Fuzzy Sets”, Fuzzy Sets and Systems, 20(1): 87-96.
• Boran, F. E., Boran, K., and Menlik, T. (2012) “The Evaluation of Renewable Energy Technologies for Electricity Generation in Turkey Using Intuitionistic Fuzzy TOPSIS”, Energy Source, Part B: Economics, Planning and Policy, 7(1): 81–90.
• Boran, F. E., Genc, S., Kurt, M. and Akay, D. (2009) “A Multi-criteria Intuitionistic Fuzzy Group Decision Making for Supplier Selection with TOPSIS Method”, Expert Systems with Applications, 36(8): 11363–11368.
• Büyüközkan, G. and Güleryüz, S. (2017) “Evaluation of Renewable Energy Sources in Turkey using an Integrated MCDM Approach with Linguistic Interval Fuzzy Preference Relations”, Energy, 123: 149-163.
• Çalı, S. and Balaman, Ş. Y. (2018) “An Entropy Based Group Decision Making Model Integrating ELECTRE and VIKOR under Intuitionistic Fuzzy Environment”, In the proceedings (book) of the XIII Balkan Conference of Operational Research, Belgrade - Serbia.
• Çelikbilek, Y. and Tüysüz, F. (2016) “An Integrated Grey based Multi-criteria Decision Making Approach for the Evaluation of Renewable Energy Sources”, Energy, 115: 1246-1258.
• Diaby, V., Campbell, K. and Goeree, R. (2013) “Multi-criteria Decision Analysis (MCDA) in Health Care: A Bibliometric Analysis”, Operations Research for Health Care, 2(1-2): 20-24.
• Erol, Ö. and Kılkış, B. (2012) “An Energy Source Policy Assessment using Analytical Hierarchy Process”, Energy Conversion and management, 63: 245-252.
• Ertay, T., Kahraman, C. and Kaya, I. (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.
• Figueira, J., Greco, S., Roy, B. and Slowi´nski, R. (2010) “ELECTRE Methods: Main Features and Recent Developments” Zopounidis, C. and Pardalos, P. M. (eds.) Handbook of Multicriteri Analysis Applied optimization, Berlin, Springer.
• Gregory, R., Failing, L., Harstone, M., Long, G., McDaniels, T. and Ohlson, D. (2012) “Structured Decision Making: A Practical Guide to Environmental Management Choices”, John Wiley & Sons.
• Hayashi, K. (2000) “Multicriteria Analysis for Agricultural Resource Management: A Critical Survey and Future Perspectives”, European Journal of Operational Research, 122(2): 486-500.
• Hung, C. C. and Chen, L. H. (2009) “A Multiple Criteria Group Decision Making Model with Entropy Weight in An Intuitionistic Fuzzy Environment”, Huang, X., Ao, SI. and Castillo, O. (eds.), Intelligent automation and computer engineering, Netherlands, Springer.
• Kahraman, C. and Kaya, İ. (2010) “A Fuzzy Multicriteria Methodology for Selection Among Energy Alternatives”, Expert Systems with Applications, 37(9): 6270-6281.
• Liu, H. C., Qin, J. T., Mao, L. X., and Zhang, Z. Y. (2014) “Personnel Selection using Interval 2-Tuple Linguistic VIKOR Method”, Human Factors and Ergonomics in Manufacturing & Service Industries, 25(3): 370-384.
• Mokhtarian, M. N., Sadi-Nezhad, S. and Makui, A. (2014) “A New Flexible and Reliable Interval Valued Fuzzy VIKOR Method Based on Uncertainty Risk Reduction in Decision Making Process: An Application for Determining A Suitable Location for Digging Some Pits for Municipal Wet Waste Landfill”, Computers & Industrial Engineering, 78: 213-233.
• Onar, S. C., Oztaysi, B., Otay, İ. and Kahraman, C. (2015) “Multi-expert Wind Energy Technology Selection using Interval-valued Intuitionistic Fuzzy Sets”, Energy, 90: 274-285.
• Opricovic, S. (1998) “Multicriteria Optimization of Civil Engineering Systems. Doctor of Philosophy Thesis, Faculty of Civil Engineering, Belgrade - Serbia.
• Opricovic, S. and Tzeng, G. H. (2007) “Extended VIKOR Method in Comparison with Outranking Methods”, European Journal of Operational Research, 178(2): 514-529.
• Roy, B. (1968) “Classement et Choix en Presence de Points de Vue Multiples (La Methode ELECTRE)”, Revue Francaise D Informatique de Recherche Operationnelle, 2(8): 57–75.
• Sevkli, M. (2010) “An Application of the Fuzzy ELECTRE Method for Supplier Selection”, International Journal of Production Research, 48(12): 3393-3405.
• Szmidt, E. and Kacprzyk, J. (2000) “Distances Between Intuitionistic Fuzzy Sets”, Fuzzy Sets and Systems, 114: 505-518.
• Şengül, Ü., Eren, M., Shiraz, S. E., Gezder, V., & Şengül, A. B. (2015) “Fuzzy TOPSIS Method for Ranking Renewable Energy Supply Systems in Turkey”, Renewable Energy, 75: 617-625.
• Vlachos, I. K. and Sergiadis, G. D. (2007) “Intuitionistic Fuzzy Information - Applications to Pattern Recognition”, Pattern Recognition Letters, 28(2): 197–206.
• Wang, J. -J., Jing, Y. -Y, Zhang, C. -F. and Zhao, J. -H. (2009) “Review on Multi-Criteria Decision Analysis Aid in Sustainable Energy Decision-Making”, Renewable and Sustainable Energy Reviews, 13(9): 2263-2278.
• Wu, M. C. and Chen, T. Y. (2011) “The ELECTRE Multicriteria Analysis Approach based on Atanassov’s Intuitionistic Fuzzy Sets”, Expert Systems with Applications, 38(10): 12318-12327.
• Xu, Z. S. (2007) “Intuitionistic Fuzzy Aggregation Operators”, IEEE Transactions on Fuzzy Systems, 15(6): 1179–1187.
• Zadeh, L. A. (1965) “Fuzzy sets”, Information and Control, 8(3): 338-353.
• Zandi, A. and Roghanian, E. (2013) “Extension of Fuzzy ELECTRE Based on VIKOR Method”, Computers & Industrial Engineering, 66(2): 258–263.
• Zeleny, M. (1976) “The Attribute-Dynamic Attitude Model”, Management Science, 23(1): 12-26.
• Zhang, H. Y., Peng, H. G., Wang, J. and Wang, J. Q. (2017) “An Extended Outranking Approach for Multi-Criteria Decision-Making Problems with Linguistic Intuitionistic Fuzzy Numbers”, Applied Soft Computing, 59: 462–474.