663 research outputs found

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

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    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

    Sustainability in Industry, Innovation and Infrastructure: A MCDM Based Performance Evaluation of European Union and Türkiye for Sustainable Development Goal 9 (SDG 9)

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    Purpose: The aim of this study is to perform two distinct cross-country evaluations including European Union (EU) countries and Türkiye, focusing on Sustainable Development Goal 9 (SDG 9): Industry, innovation and infrastructure. The study aims to obtain rankings that display the relative standings of countries and identify areas for potential enhancement. Methodology: An integrated objective criteria weighting, VIKOR, and MAIRCA based Multi-Criteria Decision Making (MCDM) approach has been employed. Findings: Based on the first analysis, high speed internet coverage (HSI) and the share of rail and inland waterways in inland freight transport (SRI) were prominent criteria, and in the MCDM analysis, Sweden displayed the highest performance, while Greece and Croatia showed the lowest performance. In the second analysis, which included Türkiye, tertiary educational attainment (TEA) criteria stood out; while, Sweden maintained its leading position. Türkiye initially had poor performance in the early years but later improved, reaching a mid-level position among 26 countries by 2020. However, a significant decline in performance was observed in the last two years. In addition, during the handled period Türkiye witnessed a decline in both the number of patent applications and the share of buses and trains in inland passenger transport. Thereby, novel policies and incentives could be formulated to overcome these issues. Originality: Two distinct cross-country analyses were conducted in accordance with the SDG 9 by adopting the most recent data and an integrated methodology. Within this context, EU countries were compared both among themselves and with Türkiye, and valuable findings were presented

    Evaluation of Factors Affecting Innovation Productivity by Pythagorean Fuzzy AHP Method

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    Purpose: In this study, it is aimed to rank the factors affecting the innovation productivity of enterprises. Methodology: The Pythagorean Fuzzy Analytical Hierarchy Process (AHP) method, which gives successful results in modelling uncertainty and uses Pythagorean fuzzy sets, is used to rank the factors affecting innovation productivity according to their importance. Findings: In the application part of study firstly, the factors affecting the innovation productivity were determined and as a result of expert evaluations, the steps of the method were applied and the factors were ranked according to their importance. Finally, the most important factors were determined by performing a sensitivity analysis. When the results obtained from the study are examined, it has been determined that the factor of preparing the technology roadmap affects the innovation productivity the most, while the sector and market structure affect the innovation productivity the least among the determined factors. Originality: It is the first study in the literature in which the factors affecting innovation productivity are determined and ranked according to their importance

    Multicriteria Decision Making in Sustainable Tourism and Low-Carbon Tourism Research: A Systematic Literature Review

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    Multicriteria Decision Making (MCDM) is increasingly being utilized as an analytical research tool for sectors that require decision-making with specific objectives and constraints, such as the tourism industry. Sustainable tourism, which examines the balance of numerous aspects, including stakeholders’ interests, is the critical feature propelling the increased usage of MCDM. This paper explores the use of Multicriteria Decision Making (MCDM) methods applied in studies of sustainable tourism and its derivative term, low-carbon tourism, using a systematic literature review (SLR) search from the Scopus database. The analysis has identified 189 relevant studies published between 1987 to April 2022. After selection, screening, and synthesizing processes, we selected 135 pertinent studies, which were analysed in general descriptive data, citation impacts, geographical categorization, categorization of the methodologies’ objectives, and possible trajectories of similar research in the future. We find that highly cited authors and articles are related to sustainable tourism indicators\u27 development and case studies. Furthermore, most relevant studies are concentrated in Asia and Europe rather than other regions. We also categorize the reviewed studies into six classifications depending on each method\u27s intended usage and further suggest four contexts for the studies’ future trajectory

    Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5

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    This fifth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered. First Part of this book presents some theoretical advances on DSmT, dealing mainly with modified Proportional Conflict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classifiers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes. Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identification of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classification. Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classification, and hybrid techniques mixing deep learning with belief functions as well

    Industry 4.0 project prioritization by using q-spherical fuzzy rough analytic hierarchy process

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    The Fourth Industrial Revolution, also known as Industry 4.0, is attracting a significant amount of attention because it has the potential to revolutionize a variety of industries by developing a production system that is fully automated and digitally integrated. The implementation of this transformation, however, calls for a significant investment of resources and may present difficulties in the process of adapting existing technology to new endeavors. Researchers have proposed integrating the Analytic Hierarchy Process (AHP) with extensions of fuzzy rough sets, such as the three-dimensional q-spherical fuzzy rough set (q-SFRS), which is effective in handling uncertainty and quantifying expert judgments, to prioritize projects related to Industry 4.0. This would allow the projects to be ranked in order of importance. In this article, a novel framework is presented that combines AHP with q-SFRS. To calculate aggregated values, the new framework uses a new formula called the q-spherical fuzzy rough arithmetic mean, when applied to a problem involving the selection of a project with five criteria for evaluation and four possible alternatives, the suggested framework produces results that are robust and competitive in comparison to those produced by other multi-criteria decision-making approaches

    AN INTEGRATED FRAMEWORK FOR QUALITY EVALUATION OF FRUITS AND VEGETABLE STORE LOCATED IN THE SUPERMARKET UNDER UTOPIAN ENVIRONMENT

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    Customer satisfaction depends on the availability of different varieties of fruits and vegetables in a supermarket store as well as the quality of this supermarket store for fruits and vegetables. The store may contain different variety of fruits and vegetables in a utopian environment. Apart from this, there are several quality parameters of a fruits and vegetable store. The quality evaluation of fruits and vegetable stores located in a supermarket is a big challenge for managerial personnel. Here, a quality evaluation framework is proposed for the fruits and vegetable store. The committee of experts identifies and finalizes the quality evaluation parameters through a brainstorming session. Fuzzy AHP is used to calculate the weights of evaluation parameters. A fuzzy TOPSIS generally ranks for the alternative stores. An improved fuzzy TOPSIS, which is named fuzzy k-TOPSIS, is proposed here to evaluate the quality of fruits and vegetable stores located in a supermarket. The fuzzy k-TOPSIS will provide rank as well as classification of the alternatives. A numerical example is demonstrated for a better understanding of the proposed framework

    Enhancing the cosmetics industry sustainability through a renewed sustainable supplier selection model

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    The cosmetics industry requires a long-term sustainable strategy to balance its continuously growing trend worldwide and its resources consumption. In this view, the suppliers' selection process is gaining more attention affecting products' overall sustainability. The objective of this contribution is hence to develop and validate the Cosmetics Sustainable Supplier Selection (C-SSS) model allowing the selection of sustainable suppliers for the cosmetic industry, evaluating them in an objective and balanced manner. The model was built relying on both scientific and grey literature, by incorporating the characteristics of existing SSS models usually used separately. The C-SSS enabled to integrate the EMM approach (to reduce the subjectivity), the ANP approach (to evaluate criteria interconnections), and the TOPSIS and ELECTRE models (to create a hybrid compensation model) to support managers in objectively selecting the most sustainable suppliers. The C-SSS model was applied and validated through an industrial use case in a cosmetics Italian company

    Similarity measure between Pythagorean fuzzy sets based on lower, upper and middle fuzzy sets with applications to pattern recognition and multicriteria decision making with PF-TODIM

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    The choice of similarity measure (SM) plays an important role in distinguishing between objects. Similarity measure of Pythagorean fuzzy sets (PFSs) is very useful and effective in discriminating between different Pythagorean fuzzy sets. Therefore, in this paper, we suggest a new similarity measure for PFSs based on converting the PFSs into their lower, upper and middle fuzzy sets (FSs) to calculate their degree of similarity. We construct an axiomatic definition for a new SM of PFSs. Furthermore, we put forward a new way to express the similarity measure of PFSs to show its competency, reliability and applicability. For establishing reasonability and usefulness of the proposed methods, we present several practical examples related to pattern recognition and multicriteria decision making problems. Finally, we construct an algorithm for Portuguese of interactive and multiple attributes decision making (TODIM) method based on the proposed similarity measures, for handling complex multicriteria decision making problems related to day to day life. Our final results show that the suggested method is reasonable, reliable and useful in managing different complex decision making problems in the context of Pythagorean fuzzy sets as the domain
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