Spherical fuzzy sets based integrated DEMATEL, ANP, VIKOR approach and its application for renewable energy selection in Turkey

被引:33
作者
Buyukozkan, Gulcin [1 ]
Karabulut, Yagmur [2 ]
Gocer, Fethullah [3 ]
机构
[1] Galatasaray Univ, Ind Engn Dept, TR-34349 Ortakay, Istanbul, Turkiye
[2] GITEC Consult, Cologne, Germany
[3] Kahramanmaras Sutcu Imam Univ, Ind Engn Dept, TR-46050 Kahramanmaras, Onikisubat, Turkiye
关键词
Renewable energy resources; Spherical fuzzy sets; Group decision making; Spherical fuzzy DEMATEL; Spherical fuzzy ANP; Spherical fuzzy VIKOR; GROUP DECISION-MAKING; PYTHAGOREAN MEMBERSHIP GRADES; MCDM MODEL; COMBINING DEMATEL; RESOURCES; PRIORITIZATION; OPTIMIZATION; TECHNOLOGIES;
D O I
10.1016/j.asoc.2024.111465
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Renewable energy continues occupying the global agenda for the low -carbon transition. Identifying suitable sources for renewable energy involves different criteria and alternatives, which can be defined as a Multi -Criteria Decision -Making (MCDM) problem. MCDM methods can be enriched with Group Decision Making (GDM) to merge individual judgments into group opinions, as well as with fuzzy sets to better simulate human opinions. To handle uncertainties of DMs' preferences, a recently developed fuzzy set extension, the Spherical Fuzzy Sets (SFSs), is combined in this study with different MCDM tools to establish a decision support tool for the energy source selection problem. This article proposes a novel MCDM approach that integrates SF-DEMATEL (Spherical Fuzzy Decision -Making Trial and Evaluation Laboratory), SF-ANP (Spherical Fuzzy Analytic Network Process), and SF-VIKOR (Spherical Fuzzy Vlse Kriterijumska Optimizacija Kompromisno Resenje) algorithms in a GDM environment and presents its application in a case study for selecting renewable energy sources in Turkey. Comparing wind, geothermal, solar, hydropower, and biogas, the proposed method highlighted both wind and solar energy as a compromise solution as the most suitable options for Turkey. It has been found that compared to similar fuzzy sets, SFS can better reflect the hesitation degree to address the lack of knowledge and errors in the membership function definitions. The robustness and plausibility of these findings are demonstrated with sensitivity and comparative analyses, suggesting this MCDM method can also be applied to similar problems in other settings.
引用
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页数:21
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