An extended DNMA-based multi-criteria decision-making method and its application in the assessment of sustainable location for a lithium-ion batteries' manufacturing plant

Prioritizing Sustainable Denim Fabric through Integrated Decision-Making Framework

In this study, a combined multi-criteria decision-making (MCDM) approach that integrates the logarithm methodology of additive weights (LMAW) and the double normalization-based multiple aggregation (DNMA) methods has been utilized to determine the optimal fabric structures considering the performance characteristics of denim fabrics containing recycled cotton. This approach focuses on sustainability and performance criteria, applying advanced decision-making methodologies to provide in-depth analysis and guidance for denim fabric selection. In this research, 15 distinct criteria were taken into account. Alternatives were ranked based on outcomes obtained from these methods. Although it was not anticipated that the top-ranked alternatives would simultaneously fulfill the beneficial or non-beneficial orientation of all criteria, an examination of the top three alternatives (A12, A5, and A15) for both garment groups revealed that they indeed aligned with the pre-determined criterion orientation. This highlights the effectiveness of the multi-criteria decision-making approach in the context of this study.

Addressing a decision problem through a bipolar Pythagorean fuzzy approach: A novel methodology applied to digital marketing

Decision-making in real-world scenarios faces uncertainty. Fuzzy theory has been a means to represent such uncertainty. In this study, we propose an approach that incorporates bipolarity into multi-criteria decision-making processes applied to digital marketing. The proposal considers both the positive and negative dimensions of data, leading to better-informed decisions. Our contribution integrates bipolarity into Pythagorean fuzzy matrices, a framework that broadens the utility of bipolar fuzzy theory. Through computational experimentation, we identify the most effective strategy for digital marketing platforms. When compared to existing techniques, our approach shows advantages, underlining its potential to improve decision-making in uncertain scenarios and offering insights for businesses that refine their digital marketing strategies.

A historical review and analysis on MOORA and its fuzzy extensions for different applications

Multi-criteria decision-making (MCDM) methods have been widely used among researchers to provide a trade-off solution between best and worst, considering conflicting criteria and sets of preferences. An efficient and systematic literature review of these methods is needed to maintain their application in distinctive domains. To this end, this paper presents a comprehensive and systematic literature survey on "multi-objective optimization by ratio analysis" (MOORA) method and its fuzzy extensions developed and discussed in recent years. This review includes articles categorized based on the publication name, publishing year, journal name, type of applications, and type of fuzzy extensions. In addition, this review will enhance the understanding of practitioners and decision-makers on the MOORA method, its development, fuzzy hybridization, different application areas, and future work. The study revealed that the MOORA technique was predominantly used with the TOPSIS approach, followed by the AHP and COPRAS methods. Furthermore, 76.28 % use single and hybridization approaches among all MOORA studies, while 23.72 % use MOORA in a fuzzy environment.