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    CODAS method using Z-fuzzy numbers
    (Ios Press, 2020) Tuysuz, Nurdan; Kahraman, Cengiz
    CODAS is a new multicriteria decision making method based on the maximum distances to negative ideal solutions, which are obtained from Euclidean and Taxicab distances. This paper develops a Z-fuzzy CODAS method based on restriction and reliability functions under uncertainty. We obtain the criteria weights from the Z-fuzzy pairwise comparison matrix. An illustrative application to supplier selection problem is also given. A comparative analysis is presented with ordinary fuzzy simple additive weighting (SAW) method.
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    COVID-19 Risk Assessment of Occupations Using Interval Type 2 Fuzzy Z-AHP & TOPSIS Methodology
    (Old City Publishing Inc, 2022) Sari, Irem Ucal; Tuysuz, Nurdan
    The pandemic spread of COVID-19 caused by a virus that affects the respiratory system represents a dramatic threat to life. People have been practicing social distancing by working from home in recent months since it is an excellent solution to reduce one's exposure to COVID-19. However, many occupations do not have this chance due to the necessity to attend the workplace. Besides, some professions require close contact with infected people such as medicine and nursing, while others such as logging and gardening have a low level of risk in this respect. However, while occupations such as medicine and nursing can take precautions against the virus at a very good level, the knowledge of occupations such as logging and gardening is weak against it. Prioritizing occupations based on these conflicting criteria is an important task under the vagueness and impreciseness of human evaluations. In this paper, a novel fuzzy AHP & TOPSIS methodology is proposed, where the reliability and restriction of the expert assessments are considered by interval-valued type 2 fuzzy numbers. A real case study including five experts, 14 occupations, and seven criteria is presented. A comparative analysis is also given to validate the proposed methodology.
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    Evaluating social sustainable development factors using multi-experts Z-fuzzy AHP
    (Ios Press, 2020) Tuysuz, Nurdan; Kahraman, Cengiz
    This study presents a multi-experts multiple criteria decision making approach for quantitatively evaluating social sustainable development factors. The proposed model which integrates Z-fuzzy numbers and fuzzy AHP enables to weight and rank social sustainable development factors, which may give guidance to many sustainable development researches. In addition to the first usage of the Z-fuzzy numbers for the weighting decision of social sustainable development factors, another contribution of the study is presenting the Z-fuzzy numbers integrated AHP method with multi-experts which can be useful in many problems and applications containing uncertainty. The most important advantage of the Z-fuzzy numbers integrated AHP method is that it allows the degree of confidence of decision makers to be included to the calculations. An application of the proposed approach is also presented for prioritizing the social sustainable development factors based on the experts' evaluations together with a sensitivity analysis.
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    An integrated picture fuzzy Z-AHP & TOPSIS methodology: Application to solar panel selection
    (Elsevier, 2023) Tuysuz, Nurdan; Kahraman, Cengiz
    AHP is the most popular multi-criteria decision-making (MCDM) method to prioritize the evaluation criteria and to rank the considered alternatives. TOPSIS method is another often used MCDM method based on negative and positive ideal solutions for the selection of the best alternative. Although the picture fuzzy extensions of the TOPSIS method are used to consider experts' hesitancy and refusal degrees in their judgments, there is a need to add reliability degrees to these judgments to provide better solutions and a reliable decision environment for real-life decision problems. This study presents a decision support tool that integrates the picture fuzzy Z-AHP (PF Z-AHP) method based on pairwise comparisons and a novel PF Z-TOPSIS method which includes reliability information for ranking the alternatives. The proposed PF Z-AHP&TOPSIS methodology is applied for solar energy panel selection problem to analyze the practicality and superiority of the methodology. The sensitivity analysis demonstrates the robustness of the proposed methodology, and the comparison analysis presents evidence that the reliability functions offered by Z-numbers have the potential to affect outcomes.
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    A novel decomposed Z-fuzzy TOPSIS method with functional and dysfunctional judgments: An application to transfer center location selection
    (Pergamon-Elsevier Science Ltd, 2024) Tuysuz, Nurdan; Kahraman, Cengiz
    Decomposed fuzzy sets (DFSs) are one of the latest extensions of intuitionistic fuzzy sets which are introduced to express vague and imprecise information to be used in multi-criteria decision-making. DFSs represent the human thinking structure in a multidirectional way, and they enable it through functional and dysfunctional judgments. However, DFSs cannot completely represent the entire human mindset as they are incapable of capturing reliability information, as it is in the other extensions, and this inability may cause wrong decisions to be given. To handle this problem, decomposed Z-fuzzy numbers, which are the integrated DFSs with reliability information provided by Z-fuzzy numbers, are introduced to model functional and dysfunctional judgments for taking the consistency of decision makers into account. Collecting judgments with both their fuzzy restrictions and fuzzy reliabilities from decision makers based on functional and dysfunctional questions provide more consistent and reliable judgments in the practice. Subsequently, a new decomposed Z-fuzzy linguistic scale and defuzzification formula are introduced to reach a final solution. Then, decomposed Z-fuzzy TOPSIS method is developed. Finally, we analyze the effect of the reliability parameter on the given decisions and present a comparative analysis with crisp TOPSIS method by an application of transfer center location selection for a private cargo company in Marmara Region of Turkey.
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    A Novel Z-Fuzzy AHP&EDAS Methodology and Its Application to Wind Turbine Selection
    (Inst Mathematics & Informatics, 2023) Tuysuz, Nurdan; Kahraman, Cengiz
    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.