An intensified linear diophantine fuzzy combined DEMATEL framework for the assessment of climate crisis

Kannan, Jeevitha; Jayakumar, Vimala; Pethaperumal, Mahalakshmi; Kather Mohideen, Ashma Banu

doi:10.1007/s00477-023-02618-7

Cited by 5 publications

(1 citation statement)

References 64 publications

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“…By utilizing IVLDF data, Petchimuthu [34] attempted to solve the supplier selection problem with its own AOs. Jeevitha et.al [24] discussed the problem of climate crisis by utilizing LDF DEMA-TEL approach. Subsequently, some enhancements of LDFS were addressed and discussed the application in the field of digital transformation [23], agri-drone [21], tender selection [22] medical diagnosis [45] Saeed et al used hybrid fuzzy hypersoft structures for optimization and efficient decisionmaking purposes [42]- [44].…”

Section: A Literature Reviewmentioning

confidence: 99%

Linear Diophantine Fuzzy Clustering Algorithm Based on Correlation Coefficient and Analysis on Logistic Efficiency of Food Products

Kannan,

Jayakumar,

Saeed

et al. 2024

IEEE Access

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The significance of clustering algorithms lies in their ability to distinguish problems and devise customized solutions. In the broader context of clustering, fuzzy clustering is one of the crucial aspects. In response to the real-world clustering problems, this research suggests a new fuzzy cluster scheme of data under the linear diophantine fuzzy set(LDFS) framework. More precisely, LDF clustering is initiated with the aid of the correlation coefficient(CC) and weighted correlation coefficient(WCC) for LDFS. Due to their ability to quantify the degree of similarity between two elements, CC are valuable in clustering problems. The LDF-clustering algorithm comprises a well-integrated algorithm for managing uncertainty and CC among LDFS. Also, our approach to LDF clustering is compared to existing fuzzy clustering studies to assess its effectiveness. Since LDFS broadens the score space, the experimental evaluation of our proposed scheme enables Decision makers(DM) to freely select their score values. The theme of this study is to impart the commencement of LDF-clustering analysis and attempt to apply CC to the clustering problem.An interpretative example provides the analysis of the logistic efficiency of food products by employing an LDF-clustering algorithm.

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Section: A Literature Reviewmentioning

confidence: 99%

Linear Diophantine Fuzzy Clustering Algorithm Based on Correlation Coefficient and Analysis on Logistic Efficiency of Food Products

Kannan,

Jayakumar,

Saeed

et al. 2024

IEEE Access

Self Cite

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Multicriteria group decision making for prioritizing IoT risk factors with linear diophantine fuzzy sets and MARCOS method

Jayakumar,

Kannan,

Kausar

et al. 2024

Granul. Comput.

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In a dynamic world of technological advances, the Internet of Things (IoT) is a transformational and widespread force that has revolutionized the way we communicate with our surroundings and regulate our environments. It offers several advantages but also introduces inherent risks. In this study, we provide a comprehensive analysis of the risks associated with IoT and employ the effectiveness of a Linear Diophantine Fuzzy Set to rank the risk factors. Because of the significant uncertainties frequently present in IoT contexts, the use of a fuzzy framework is invaluable in discerning and addressing these risks. The primary contribution is to employ the Measurement of Alternatives and Ranking according to the Compromise Solution (MARCOS) method and linear diophantine fuzzy sets to propose a multi-criteria group decision-making method (MCGDM) for ranking attributes to facilitate risk prioritization, enabling consumers to determine the crucial hazards in their IoT systems. Furthermore, we implement a comparative study and a sensitivity analysis to demonstrate the robustness of our proposed methodology. The insights obtained from our research not only improve the awareness of IoT hazards but also enable organizations and individuals to make informed decisions when navigating IoT fields. By proactively addressing these risks, we endorse the development and secure deployment of IoT technology.

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Circular product design strategies in the apparel industry: toward the circular economy

Rahee,

Sarker

2024

Discov Sustain

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The design stage of a product plays a critical role in determining its sustainability. Key product attributes—such as reliability, durability, reusability, repairability, design for remanufacturing, recyclability, and end-of-life considerations—are established during this stage, influencing the product’s overall environmental impact. Circular product design (CPD) is a design philosophy that fosters economic growth while reducing negative environmental impact across the product’s entire life cycle. This study aims to identify circular product design strategies (CPDS) for the apparel industry, a sector known for its significant carbon footprint. Twelve CPDS are identified in this study, categorized into five dimensions of circular economy (CE): narrowing, slowing, closing, reintegrating, and technology, using the fuzzy Delphi method (FDM) with inputs from a panel of twenty-three experts. Furthermore, causal interrelationships and a prioritized list of these strategies are determined using the fuzzy decision-making trial and evaluation laboratory (DEMATEL) technique. Of the twelve strategies, five are part of the causal group, while the remainder are in the effect group. The top three causal CPDS are Design standardization, Design with responsible materials, and Design for redesign and remanufacturing. Conversely, the CPDS under the ‘effect’ group with least impact includes Multifunctional product design, Artificial intelligence in design forecasting, and Computer-aided product design. This study offers valuable managerial insights for decision-makers and designers in the apparel industry, guiding the implementing of CE practices throughout the apparel supply chain.

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An intensified linear diophantine fuzzy combined DEMATEL framework for the assessment of climate crisis

Cited by 5 publications

References 64 publications

Linear Diophantine Fuzzy Clustering Algorithm Based on Correlation Coefficient and Analysis on Logistic Efficiency of Food Products

Linear Diophantine Fuzzy Clustering Algorithm Based on Correlation Coefficient and Analysis on Logistic Efficiency of Food Products

Multicriteria group decision making for prioritizing IoT risk factors with linear diophantine fuzzy sets and MARCOS method

Circular product design strategies in the apparel industry: toward the circular economy

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