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Journal of Industrial and Systems Engineering، جلد ۸، شماره ۲، صفحات ۵۴-۶۶
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عنوان انگلیسی A new last aggregation compromise solution approach based on TOPSIS method with hesitant fuzzy setting to energy policy evaluation
چکیده انگلیسی مقاله 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.
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نویسندگان مقاله معصومه موسوی |
department of energy economics, economics faculty, university of tehran, tehran, iran
سازمان اصلی تایید شده: دانشگاه تهران (Tehran university)

رضا توکلی مقدم | reza tavakkoli
school of industrial engineering, college of engineering, university of tehran, tehran, iran
سازمان اصلی تایید شده: دانشگاه تهران (Tehran university)

نشانی اینترنتی http://www.jise.ir/article_8744_00a3d5bbf6a2cc7b5b4c3f2522bf0f08.pdf
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