Yazar "Kahraman, Cengiz" seçeneğine göre listele

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    ERP selection using picture fuzzy CODAS method
    (Ios Press, 2021) Aydogmus, Hacer Yumurtaci; Kamber, Eren; Kahraman, Cengiz
    The purpose of this study is to develop an extension of CODAS method using picture fuzzy sets. In this respect, a new methodology is introduced to figure out how picture fuzzy numbers can be applied to CODAS method. COmbinative Distance-based Assessment (CODAS) is a new MCDM method proposed by Ghorabaee et al. Picture fuzzy sets (PFSs) are a new extension of ordinary fuzzy sets for representing human's judgments having possibility more than two answers such as yes, no, refusal and neutral. Compared with other studies, the proposed method integrates multi-criteria decision analysis with picture fuzzy uncertainty based on Euclidean and Taxicab distances and negative ideal solution. ERP system selection problem is handled as the application area of the developed method, picture fuzzy CODAS. Results indicate that the new proposed method finds meaningful rankings through picture fuzzy sets. Comparative analyzes show that the presented method gives successful and robust results for the solutions of MCDM problems under fuzziness.
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    Öğe
    Prioritization of drip-irrigation pump alternatives in agricultural applications: An integrated picture fuzzy BWM&CODAS methodology
    (Elsevier, 2024) Kamber, Eren; Aydogmus, Ufuk; Aydogmus, Hacer Yumurtaci; Guemues, Mehmet; Kahraman, Cengiz
    One of the irrigation methods is drip irrigation, for which selecting the right pump has a significant impact. In this study, the process of choosing the appropriate pump for drip irrigation is regarded as a multi-criteria decision-making (MCDM) problem. The objective is to enhance productivity and minimize water consumption in agricultural areas by addressing the drip-irrigation pump-selection problem. Making decisions under uncertainty is a complex task, especially when dealing with intricate problems where complexity raises concerns about finding more dependable solutions. Fuzzy extensions of MCDM methods are designed to tackle such intricate and detailed problems compared to traditional MCDM methods. Therefore, we propose and implement a Picture Fuzzy CODAS (PF-CODAS) method to address the issue of drip-irrigation pump selection under vagueness, utilizing expert opinions. In comparison to other MCDM methods, our suggested approach combines multi-criteria decision analysis with picture fuzzy hesitancy and a negative ideal solution, supported by Euclidean and Taxicab distances. Furthermore, we present an integrated approach that uses the Best Worst Method (BWM) to determine criterion weights and the PF-CODAS method for ranking alternatives. Overall, this study offers valuable support for advancing sustainable agriculture through our proposed MCDM approach.