A Benchmark Similarity Measures for Fermatean Fuzzy Sets

In this paper, we utilized triangular conorms (S-norm). The essence of using S-norm is that the similarity order does not change using different norms. In fact, we are investigating for a new conception for calculating the similarity of two Fermatean fuzzy sets. For this purpose, utilizing an S-norm, we first present a formula for calculating the similarity of two Fermatean fuzzy values, so that they are truthful in similarity properties. Following that, we generalize a formula for calculating the similarity of the two Fermatean fuzzy sets which prove truthful in similarity conditions. Finally, various numerical examples have been presented to elaborate this method

A Comprehensive Review of the Novel Weighting Methods for Multi-Criteria Decision-Making

In the realm of multi-criteria decision-making (MCDM) problems, the selection of a weighting method holds a critical role. Researchers from diverse fields have consistently employed MCDM techniques, utilizing both traditional and novel methods to enhance the discipline. Acknowledging the significance of staying abreast of such methodological developments, this study endeavors to contribute to the field through a comprehensive review of several novel weighting-based methods: CILOS, IDOCRIW, FUCOM, LBWA, SAPEVO-M, and MEREC. Each method is scrutinized in terms of its characteristics and steps while also drawing upon publications extracted from the Web of Science (WoS) and Scopus databases. Through bibliometric and content analyses, this study delves into the trend, research components (sources, authors, countries, and affiliations), application areas, fuzzy implementations, hybrid studies (use of other weighting and/or ranking methods), and application tools for these methods. The findings of this review offer an insightful portrayal of the applications of each novel weighting method, thereby contributing valuable knowledge for researchers and practitioners within the field of MCDM.WOS:0009972313000012-s2.0-85160203389Emerging Sources Citation IndexarticleUluslararası işbirliği ile yapılan - EVETHaziran2023YÖK - 2022-2

Analysis of the Trade Performance of the European Union and Serbia on the Base of FF-WASPAS and WASPAS Methods

In this paper, based on a multicriteria analysis, the trade performance of selective countries of the European Union and Serbia is reviewed. In this paper, based on a multicriteria analysis, the trade performance of selective countries of the European Union and Serbia is reviewed.According to the results of the FF-WASPAS method, Germany's trade ranks first in terms of performance. They are followed by: France, Italy, Hungary, Greece, Croatia, Slovenia, Austria, Serbia, Bulgaria and Romania. Croatia's trade performance is better than Slovenia's. According to the results of the FF-WASPAS method, Serbia is in a worse position than Croatia and Slovenia. According to the results of the classic WASPAS method, Germany's trade ranks first in terms of performance. Followed by: Italy, France, Greece, Romania, Bulgaria, Hungary, Austria, Serbia, Croatia and Slovenia. The leading countries of the European Union (Germany, France and Italy) are among the top five countries (along with Greece and Romania). Serbia is in a better position compared to Croatia and Slovenia. Numerous factors influenced the performance positioning of trade between the European Union and Serbia: economic climate, foreign direct investments, asset management, new business models (multichannel sales, private label, sales of organic products), new concepts of cost, sales and profit management (cost calculation by activity, customer management, product category management, etc.), the Covid-19 pandemic, the energy crisis, etc. A key factor is the digitization of the entire business. The target profit can be achieved by adequately controlling them

APPLICATION OF HYBRID DIBR-FUCOM-LMAW-BONFERRONI-GREY-EDAS MODEL IN MULTICRITERIA DECISION-MAKING

The selection of unmanned aerial vehicles for different purposes is a frequent topic of research. This paper presents a hybrid model of an unmanned aerial vehicle (UAV) selection using the Defining Interrelationships Between Ranked criteria (DIBR), Full Consistency Method (FUCOM), Logarithm Methodology of Additive Weights (LMAW) and grey - Evaluation based on Distance from Average Solution (G-EDAS) methods. The above-mentioned model is tested and confirmed in a case study. First of all, in the paper are defined the criteria conditioning the selection, and then with the help of experts and by applying the DIBR, FUCOM and LMAW methods, the weight coefficients of the criteria are determined. The final values of the weight coefficients are obtained by aggregating the values of the criteria weights from all the three methods using the Bonferroni aggregator. Ranking and selection of the optimal UAV from twenty-three defined alternatives is carried out using the G-EDAS method. Sensitivity analysis confirmed a high degree of consistency of the solutions obtained using other MCDM methods, as well as changing the criteria weight coefficients. The proposed model has proved to be stable; its application is also possible in other areas and it is a reliable tool for decision-makers during the selection process

A decision-making framework based on the Fermatean hesitant fuzzy distance measure and TOPSIS

A particularly useful assessment tool for evaluating uncertainty and dealing with fuzziness is the Fermatean fuzzy set (FFS), which expands the membership and non-membership degree requirements. Distance measurement has been extensively employed in several fields as an essential approach that may successfully disclose the differences between fuzzy sets. In this article, we discuss various novel distance measures in Fermatean hesitant fuzzy environments as research on distance measures for FFS is in its early stages. These new distance measures include weighted distance measures and ordered weighted distance measures. This justification serves as the foundation for the construction of the generalized Fermatean hesitation fuzzy hybrid weighted distance (DGFHFHWD) scale, as well as the discussion of its weight determination mechanism, associated attributes and special forms. Subsequently, we present a new decision-making approach based on DGFHFHWD and TOPSIS, where the weights are processed by exponential entropy and normal distribution weighting, for the multi-attribute decision-making (MADM) issue with unknown attribute weights. Finally, a numerical example of choosing a logistics transfer station and a comparative study with other approaches based on current operators and FFS distance measurements are used to demonstrate the viability and logic of the suggested method. The findings illustrate the ability of the suggested MADM technique to completely present the decision data, enhance the accuracy of decision outcomes and prevent information loss

Multiple attribute decision-making based on Fermatean fuzzy number

Multiple attribute decision-making concerns with production significant in our everyday life. To resolve the problems that decision makers might feel uncertain to choose the suitable assessment values among several conceivable ideals in the procedure. Fuzzy model, and its extensions are extensively applied to MADM problems. In this study, we proposed an innovative Schweizer-Sklar t-norm and t-conorm operation of FFNs, Fermatean fuzzy Schweizer-Sklar operators. They were used as a framework for the development of an MCDM method, which was illustrated by an example to demonstrate its effectiveness and applicability. Finally, a complete limitation study, rational examination, and comparative analysis of the presented approaches has been exhibited, we originate that our technique is superior in offering DMs a better decision-making choice and reducing the restrictions on stating individual partialities

Computation of Choquet integral for finite sets: Notes on a ChatGPT-driven experience

The Choquet integral, credited to Gustave Choquet in 1954, initially found its roots in decision making under uncertainty following Schmeidler's pioneering work in this field. Surprisingly, it was not until the 1990s that this integral gained recognition in the realm of multi-criteria decision aid. Nowadays, the Choquet integral boasts numerous generalizations and serves as a focal point for intensive research and development across various domains. Here we share our journey of utilizing ChatGPT as a helpful assistant to delve into the computation of the discrete Choquet integral using Mathematica. Additionally, we have demonstrated our ChatGPT experience by crafting a Beamer presentation with its assistance. The ultimate aim of this exercise is to pave the way for the application of the discrete Choquet integral in the context of N-soft sets

Correlation Coefficients of Fermatean Fuzzy Sets with a Medical Application

The FFS is an influential extension of the available IFS and PFS, whose benefit is to better exhaustively characterize ambiguous information. For FFSs, the correlation between them is usually evaluated by the correlation coefficient. To reflect the perspective of professionals, in this paper, a new correlation coefficient of FFSs is proposed and investigated. The correlation coefficient is very important and frequently used in every field from engineering to economics, from technology to science. In this paper, we propose a new correlation coefficient and weighted correlation coefficient formularization to evaluate the affair between two FFSs. A numerical example of diagnosis has been gotten to represent the efficiency of the presented approximation. Outcomes calculated by the presented approximation are compared with the available indices

Evaluation of risks impeding sustainable mining using Fermatean fuzzy score function based SWARA method

Sustainability in the mining and raw materials sector is a key target in the EU Green deal agenda. The aim of this work is to determine the degree of importance of risks that may impede sustainable mining, considering UN Sustainable Development Goals (SDGs) indicators and EU initiatives, taking as a case study the mining sector in Greece. A total of 49 risks for sustainable mining, under six categories, were identified by means of expert consultation and review of the literature. The identification and prioritization of potential risks can provide a pathway towards sustainable mining operations. The risks factors weighting is enhanced using a new Fermatean fuzzy score function with Stepwise Weight Assessment Ratio Analysis (SWARA). The proposed model is a powerful tool to handle the uncertainties and inaccuracies in the information regarding the weights of the risks. The main research findings indicate that the most important risks for sustainable mining in Greece are irresponsible mining, the lack of license to operate, and poor environmental monitoring, which are directly connected to the aim and scope of SDG12: responsible consumption and production. In addition, according to the results the category with the highest risk for sustainable mining is the one of “Risk to Environment”. A complete list of risks and risk categories, and their ranking is presented and discussed creating a priority of actions in the framework of European and international initiatives to set a road map to sustainable mining. This work provides a benchmark for future studies, with the aim of providing a tool for evaluating and ranking global risk factors that may affect sustainable mining development

Notes on soft sets and aggregation operators

[EN]Under uncertainty, traditional sets may not be sufficient to represent real-world phenomena, and fuzzy sets can provide a more flexible and natural approach. The concept of fuzzy sets has been widely used in various fields, including artificial intelligence, control theory, decision-making, and pattern recognition. Fuzzy sets can also be combined with other mathematical tools, such as probability theory, to provide a more comprehensive approach to uncertainty management. In these notes, we explore the concept of fuzzy sets under uncertainty, and their applications in various fields. We discuss the fundamental concepts of fuzzy sets, including fuzzy membership functions, fuzzy operations, and fuzzy relations. We also examine different types of uncertainty, including epistemic and aleatory uncertainty, and how fuzzy sets can be used to model and manage uncertainty in these cases