A new last aggregation compromise solution approach based on TOPSIS method with hesitant fuzzy setting to energy policy evaluation

Document Type: Research Paper

Authors

1 Department of Energy Economics, Economics Faculty, University of Tehran, Tehran, Iran

2 School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran

Abstract

Utilizing renewable energies is identified as one of significant issues for economical and social significance in future human life. Thus, choosing the best renewable energy among renewable energy candidates is more important. To address the issue, multi-criteria group decision making (MCGDM) methods with imprecise information could be employed to solve these problems. The aim of this paper is to propose a new compromise solution approach based on technique for order preference by similarity to ideal solution (TOPSIS) method under evaluations of a group of experts with hesitant fuzzy information. The hesitant fuzzy set (HFS) is a modern fuzzy set which could help the experts by providing some membership degrees for renewable energy candidates under the evaluation criteria to margin of errors. Also, weights of each expert and criterion are determined by proposing extended hesitant fuzzy entropy and maximizing deviation methods based on hesitant fuzzy Euclidean-Hausdorff distance measure. In addition, the judgments (preferences) of experts are aggregated in the final step to prevent the loss of data. Finally, an illustrative example about the energy policy selection is presented to demonstrate the procedure of the proposed decision approach. Also, a comparative analysis is provided with the recent decision method of the literature to show the capability of the proposed approach.

Keywords

Main Subjects


Afgan, Naim H and Maria G Carvalho. (2002). Multi-criteria assessment of new and renewable
energy power plants. Energy, 27: 739-755.
Akash, Bilal A, Rustom Mamlook and Mousa S Mohsen. (1999). Multi-criteria selection of electric
power plants using analytical hierarchy process. Electric power systems research, 52: 29-35.
Ansari, Asif Jamil and Imtiaz Ashraf. (2012). Best Energy Option Selection using Fuzzy Multicriteria
Decision Making Approach. International Journal of Advanced Renewable Energy
Researches (IJARER), 1.
Cavallaro, Fausto. (2013). Assessment of Nuclear Energy Competiveness Using a Multi-Criteria
Fuzzy Approach. International Journal of Energy Optimization and Engineering (IJEOE), 2: 21-36.
Doukas, Haris, Anastasia Tsiousi, Vangelis Marinakis and John Psarras. (2014). Linguistic multicriteria
decision making for energy and environmental corporate policy. Information Sciences, 258:
328-338.
Erol, Özgür and Birol Kılkıs. (2012). An energy source policy assessment using analytical hierarchy
process. Energy Conversion and management, 63: 245-252.

Georgiou, Dimitris, Essam Sh Mohammed and Stelios Rozakis. (2015). Multi-criteria decision
making on the energy supply configuration of autonomous desalination units. Renewable Energy, 75:
459-467.
Goumas, M and V Lygerou. (2000). An extension of the PROMETHEE method for decision making
in fuzzy environment: Ranking of alternative energy exploitation projects. European Journal of
Operational Research, 123: 606-613.
Jing, You-Yin, He Bai and Jiang-Jiang Wang. (2012). A fuzzy multi-criteria decision-making model
for CCHP systems driven by different energy sources. Energy Policy, 42: 286-296.
Kaya, Tolga and Cengiz Kahraman. (2011). Multicriteria decision making in energy planning using a
modified fuzzy TOPSIS methodology. Expert Systems with Applications, 38: 6577-6585.
Kaya, Tolga and Cengiz Kahraman.(2010). Multicriteria renewable energy planning using an
integrated fuzzy VIKOR & AHP methodology: The case of Istanbul. Energy, 35: 2517-2527.
Kaygusuz, Kamil. (2002). Environmental impacts of energy utilisation and renewable energy policies
in Turkey. Energy Policy, 30: 689-698.
Keyhani, A, M Ghasemi-Varnamkhasti, M Khanali and R Abbaszadeh 2010. An assessment of wind
energy potential as a power generation source in the capital of Iran, Tehran. Energy, 35: 188-201.
Meixner, Oliver. (2009). Fuzzy AHP group decision analysis and its application for the evaluation of
energy sources. In Proceedings of the 10th International Symposium on the Analytic
Hierarchy/Network Process Multi-criteria Decision Making.
Patlitzianas, Konstantinos D, Konstantinos Ntotas, Haris Doukas and John Psarras. (2007). Assessing
the renewable energy producers’ environment in EU accession member states. Energy Conversion
and Management, 48: 890-897.
Sadeghi, Arash, Taimaz Larimian and Ali Molabashi. (2012). Evaluation of renewable energy sources
for generating electricity in province of Yazd: a fuzzy MCDM approach. Procedia-Social and
Behavioral Sciences, 62: 1095-1099.
Sianaki, Omid Ameri and Mohammad AS Masoum. (2013). A multi-agent intelligent decision making
support system for home energy management in smart grid: A fuzzy TOPSIS approach. Multiagent
and Grid Systems, 9: 181-195.
Torra, Vicenç. (2010). Hesitant fuzzy sets. International Journal of Intelligent Systems, 25: 529-539.
Torra, Vicenç and Yasuo Narukawa. (2009). On hesitant fuzzy sets and decision. In On hesitant fuzzy
sets and decision, Fuzzy Systems, 2009. FUZZ-IEEE 2009. IEEE International Conference , 1378-
1382: IEEE.
Ulutas, Berna Haktanırlar. (2005). Determination of the appropriate energy policy for Turkey. Energy,
30: 1146-1161.
Wang, Bing, Dundar F Kocaoglu, Tugrul U Daim and Jiting Yang. (2010). A decision model for
energy resource selection in China. Energy Policy, 38: 7130-7141.
Wang, Jian Qiang, Dan Dan Wang, Hong yu Zhang and Xiao Hong Chen. (2014). Multi-criteria
outranking approach with hesitant fuzzy sets. OR Spectrum, 36: 1001-1019.

Wu, Jia-ting, Jian-qiang Wang, Jing Wang, Hong-yu Zhang and Xiao-hong Chen. (2014). Hesitant
Fuzzy Linguistic Multicriteria Decision-Making Method Based on Generalized Prioritized
Aggregation Operator. The Scientific World Journal, 2014.
Xia, Meimei and Zeshui Xu. (2011). Hesitant fuzzy information aggregation in decision making.
International Journal of Approximate Reasoning, 52: 395-407.
Xu, Zeshui and Meimei Xia. (2011). Distance and similarity measures for hesitant fuzzy sets.
Information Sciences, 181: 2128-2138.
Xu, Zeshui and Xiaolu Zhang. (2013). Hesitant fuzzy multi-attribute decision making based on
TOPSIS with incomplete weight information. Knowledge-Based Systems, 52: 53-64.
Yazdani-Chamzini, Abdolreza, Mohammad Majid Fouladgar, Edmundas Kazimieras Zavadskas and S
Hamzeh Haji Moini. (2013). Selecting the optimal renewable energy using multi criteria decision
making. Journal of Business Economics and Management, 14: 957-978.
Zamani, Mehrzad. (2007). Energy consumption and economic activities in Iran. Energy Economics,
29: 1135-1140.
Zhu, Bin, Zeshui Xu and Meimei Xia. (2012). Hesitant fuzzy geometric Bonferroni means.
Information Sciences, 205: 72-85.