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A Novel Z-Fuzzy AHP&EDAS Methodology and Its Application to Wind Turbine Selection
Volume 34, Issue 4 (2023), pp. 847–880
Pub. online: 30 March 2023      Type: Research Article      Open accessOpen Access
Received
1 November 2022
Accepted
1 March 2023
Published
30 March 2023

Abstract

Modelling the reliability information in decision making process is an important issue to inclusively reflect the thoughts of decision makers. The Evaluation Based on Distance from Average Solution (EDAS) and Analytic Hierarchy Process (AHP) are frequently used MCDM methods, yet their fuzzy extensions in the literature are incapable of representing the reliability of experts’ fuzzy preferences, which may have important effects on the results. The first goal of this study is to extend the EDAS method by using Z-fuzzy numbers to reinforce its representation ability of fuzzy linguistic expressions. The second goal is to propose a decision making methodology for the solution of fuzzy MCDM problems by using Z-fuzzy AHP method for determining the criteria weights and Z-fuzzy EDAS method for the selection of the best alternative. The contribution of the study is to present an MCDM based decision support tool for the managers under vague and imprecise data, which also considers the reliability of these data. The applicability of the proposed model is presented with an application to wind energy investment problem aiming at the selection of the best wind turbine. Finally, the effectiveness and competitiveness of the proposed methodology is demonstrated by making a comparative analysis with the Z-fuzzy TOPSIS method. The results show that the proposed methodology can not only represent experts’ evaluation information extensively, but also reveal a logical and consistent sequence related to wind turbine alternatives using reliability information.

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Biographies

Tüysüz Nurdan
https://orcid.org/0000-0002-0913-8351
yildizn18@itu.edu.tr

N. Tüysüz received her BSc in industrial engineering in 2013 from Konya Selçuk University and her MSc in industrial engineering from Istanbul University, in 2017. She has been a PhD candidate in Department of Industrial Engineering at Istanbul Technical University since 2018. She is currently working as a research assistant at Istanbul Gelisim University. Her research interests include fuzzy sets and their extensions, decision theory and system simulation.

Kahraman Cengiz
https://orcid.org/0000-0001-6168-8185
kahramanc@itu.edu.tr

C. Kahraman is a full professor at Istanbul Technical University. His research areas are engineering economics, quality management, statistical decision making, multicriteria decision making, and fuzzy decision making. He published about 300 international journal papers and about 200 conference papers. He became the guest editor of many international journals and the editor of many international books from Springer. He is a member of editorial boards of 20 international journals. He is the chair of INFUS International Conferences on fuzzy and intelligent systems ZS, Yager RR, some geometric aggregation operators based on intuitionistic fuzzy sets.


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AHP EDAS Z-fuzzy restriction function reliability renewable energy

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