Article
Multidisciplinary Sciences
Zahid Hussain, Sahar Abbas, Miin-Shen Yang
Summary: In this article, the q-rung orthopair fuzzy sets (q-ROFSs) are introduced as a novel and rigorous generalization of fuzzy sets. The construction of a measure of similarity between q-ROFSs based on the Hausdorff metric is presented, along with some axiomatic definitions of distances and similarity measures. Numerical examples and an algorithm for orthopair fuzzy TODIM are provided to demonstrate the usefulness of the proposed similarity measures in pattern recognition, queries with fuzzy linguistic variables, and multi-criteria decision making.
Article
Mathematics, Applied
M. Riyahi, A. Borumand Saeid, M. Kuchaki Rafsanjani
Summary: This paper introduces a novel reduction strategy to improve fuzzy sets by tackling the drawbacks of existing methods. The strategy reduces the value of grades by finding a proper power automatically and reduces the other grades based on their distance with the maximum grade. Mathematically, it is proven that the ratio between the grades before and after the reduction process will remain intact, solving the problem of information loss. The higher accuracy level of the novel strategy is demonstrated through various examples compared to the preceding methods, q-rung orthopair and T-sipherical fuzzy sets.
IRANIAN JOURNAL OF FUZZY SYSTEMS
(2022)
Article
Mathematics
Mailing Zhao, Jun Ye
Summary: This study proposes an orthopair Z-number (OZN) set to depict the truth and falsehood values of fuzzy values and their reliability levels. The established operators and multiattribute decision-making model demonstrate the superiority of the proposed model in reliability and flexibility of decision results.
JOURNAL OF MATHEMATICS
(2021)
Article
Computer Science, Artificial Intelligence
Lei Zhou, Kun Gao
Summary: Three novel pseudometrics on the set of intuitionistic fuzzy numbers are proposed in this paper, and a unified method to calculate the distances between different types of intuitionistic fuzzy sets based on these pseudometrics is introduced, along with corresponding proofs.
Article
Mathematics, Applied
Admi Nazra, Jenizon, Yudiantri Asdi, Zulvera
Summary: This article introduces a new hybrid model called hesitant intuitionistic fuzzy N-soft sets (HIFNSSs), which combines intuitionistic fuzzy N-soft sets and hesitant fuzzy N-soft sets. In addition, HIFNSSs are generalized to generalized hesitant intuitionistic fuzzy N-soft sets (GHIFNSSs), serving as a hybrid model between generalized hesitant intuitionistic fuzzy sets and N-soft sets.
Article
Mathematics
Zeeshan Ali, Tahir Mahmood, Miin-Shen Yang
Summary: In this paper, the authors derive the Frank operational laws for CIF information and propose prioritized aggregation operators based on these laws. They also introduce the WASPAS method under the consideration of CIF information and provide numerical examples to compare the proposed operators with existing ones in multi-attribute decision-making procedures, demonstrating the validity and worth of the proposed approaches.
Article
Computer Science, Information Systems
Kamal Kumar, Shyi-Ming Chen
Summary: In this paper, a new multiple attribute group decision making method based on linguistic intuitionistic fuzzy numbers is proposed. The method overcomes the drawbacks of existing methods and provides a useful approach for decision-making in linguistic intuitionistic fuzzy environments.
INFORMATION SCIENCES
(2022)
Article
Mathematics
Stoyan Poryazov, Velin Andonov, Emiliya Saranova, Krassimir Atanassov
Summary: This paper investigates the use of intuitionistic fuzzy pairs as uncertainty estimations in service systems. Three intuitionistic fuzzy characterizations of virtual service devices are specified. Two approaches to the intuitionistic fuzzy estimation of the uncertainty of service compositions are discussed, one based on the definitions of intuitionistic fuzzy pairs for one service device, and the other based on aggregation operators over intuitionistic fuzzy pairs. Six intuitionistic fuzzy estimations of the uncertainty of service device compositions are proposed.
Article
Computer Science, Information Systems
Tahir Mahmood, Jabbar Ahmmad, Zeeshan Ali, Miin-Shen Yang
Summary: Due to the complexities of different diseases, accurate medical diagnosis has become a difficult task for experts. Researchers are developing new methods to overcome these difficulties. This article proposes novel techniques to aid experts in accurately diagnosing diseases, including the establishment of confidence-level intuitionistic fuzzy aggregation operators and a medical diagnosis model based on the intuitionistic fuzzy rough model.
Article
Computer Science, Artificial Intelligence
J. Reegan Jebadass, P. Balasubramaniam
Summary: Image fusion is a technique for improving image quality by extracting critical information. The proposed method based on intuitionistic fuzzy sets converts given images into fuzzy images and then into interval type-2 fuzzy images, achieving the best visual quality and performance evaluation results.
APPLIED SOFT COMPUTING
(2023)
Article
Green & Sustainable Science & Technology
Xumei Yuan, Cuicui Zheng
Summary: This paper proposes a general expression of intuitionistic fuzzy entropy based on special functions to measure the fuzziness of intuitionistic fuzzy sets (IFSs). The effectiveness and practicability of this entropy in decision making are verified by comparing it with other entropy measures.
Article
Mathematics
R. Mareay, Ibrahim Noaman, Radwan Abu-Gdairi, M. Badr
Summary: This study introduces three models of intuitionistic fuzzy set approximation space based on covering, and proves the definitions and features using the notion of the neighborhood.
Article
Green & Sustainable Science & Technology
Oguz Emir, Sule Onsel Ekici
Summary: In recent years, waste management has gained attention due to sustainability concerns and the depletion of natural resources. Food waste management is particularly important given the growing population and hunger crisis. Integrated assessment models (IAMs) have been commonly used to study food waste and provide insights to policymakers, while the Fuzzy Cognitive Map (FCM) extended with intuitionistic fuzzy sets offers a framework for analyzing interactions between factors and prioritizing policies.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Multidisciplinary Sciences
Xiaofeng Wen, Xiaohong Zhang, Tao Lei
Summary: In this paper, the concept of intuitionistic fuzzy overlap function is proposed for the first time, and its generating method, representable and unrepresentable examples are given. A new class of intuitionistic fuzzy rough set model is established using the IF-overlap function, leading to an improved TOPSIS method. The flexibility and effectiveness of the new method are demonstrated through comparative analysis.
Article
Physics, Multidisciplinary
Pavel Sevastjanov, Ludmila Dymova, Krzysztof Kaczmarek
Summary: In this paper, a critical analysis of Neutrosophic, Pythagorean, and other novel fuzzy sets theories is provided, revealing shortcomings and proposing alternative approaches for improvement. The author suggests extending intuitionistic fuzzy sets within the framework of the Dempster-Shafer theory to address the internal problems of Atanassov's intuitionistic fuzzy sets and enhance upon them.
Article
Computer Science, Artificial Intelligence
James Izzard, Fabio Caraffini, Francisco Chiclana
Summary: This paper presents a software solution for designing general meal plans based on user's nutritional characteristics. Existing literature lacks a software solution in its most general form for this problem. The proposed software model is flexible and equipped with a simple optimization algorithm for the prototype system. Results from ten test problems suggest that the prototype system can address the general meal optimization problem.
APPLIED INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Kai Xiong, Yucheng Dong, Zhaoxia Guo, Francisco Chiclana, Enrique Herrera-Viedma
Summary: This study aims to explore the ranking, classifications, and evolution mechanisms of research fronts in the Web of Science Essential Science Indicators (ESI) database using a multiattribute decision-making (MADM) and clustering method. The study reveals the performance differences between different countries and identifies the USA and China as the leading countries in most research fronts.
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
(2023)
Article
Engineering, Industrial
Yucheng Dong, Siqi Wu, Xiaoping Shi, Yao Li, Francisco Chiclana
Summary: This article investigates the clustering of failure modes based on their risks in FMEA practice. It proposes the additive N-clustering problem and explores the characteristics of exogenous clustering methods and endogenous clustering methods. It also introduces the Consensus-based ENdogenous Clustering Method (CENCM) as a solution for cases where accurate category thresholds are difficult to provide, and validates its effectiveness through comparisons and simulation experiments.
Article
Management
Tiantian Gai, Mingshuo Cao, Francisco Chiclana, Zhen Zhang, Yucheng Dong, Enrique Herrera-Viedma, Jian Wu
Summary: This paper proposes a consensus-trust driven framework for bidirectional interaction in social network large-group decision making. The framework includes defining interaction consensus threshold and interaction trust threshold, designing hybrid feedback strategies, and developing a minimum adjustment bidirectional feedback model considering cohesion. The effectiveness and applicability of the model are demonstrated through its application to a blockchain platform selection problem in supply chain.
GROUP DECISION AND NEGOTIATION
(2023)
Article
Computer Science, Artificial Intelligence
Qi Sun, Jian Wu, Francisco Chiclana, Sha Wang, Enrique Herrera-Viedma, Ronald R. Yager
Summary: In the problem of social network group decision making, this paper proposes a theoretical framework to prevent weight manipulation behavior by utilizing community detection and power index measurement. Through the combination of minimum adjustment and maximum entropy rules, the proposed method ensures the rationality and fairness of weight distribution, achieving consensus efficiently.
ARTIFICIAL INTELLIGENCE REVIEW
(2023)
Article
Computer Science, Artificial Intelligence
Feixia Ji, Jian Wu, Francisco Chiclana, Sha Wang, Hamido Fujita, Enrique Herrera-Viedma
Summary: This study proposes an overlapping community-driven feedback mechanism to improve consensus in social network group decision making. By guiding inconsistent subgroups to interact with each other and selecting personalized feedback parameters, this mechanism helps achieve higher levels of consensus.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Carlos Saenz-Royo, Francisco Chiclana, Enrique Herrera-Viedma
Summary: Expert judgments are crucial in decision theory, but the criterion for selecting experts remains an unresolved issue. This paper proposes a simulation methodology to assess the cost-benefit of decision support techniques and examines the impact of imposing consistency as a criterion for selecting experts. The findings suggest that the use of Saaty's consistency criterion can lead to a maximum 5% increase in the expected payoff of the Analytical Hierarchy Process (AHP) decision support technique.
INFORMATION FUSION
(2023)
Article
Computer Science, Artificial Intelligence
Weiqiao Liu, Jianjun Zhu, Francisco Chiclana
Summary: Large-scale group decision-making requires subgroup division and representative selection to reach consensus, but few consensus optimization models consider the issue of selecting subgroup representatives. This article proposes a consensus hybrid strategy framework with three-dimensional clustering optimization using normal cloud models to represent experts' imprecise preferences in complex decision scenarios. It establishes a clustering optimization method to select representatives based on preference similarity, precision, and consistency levels, and provides two consensus recommendation optimization strategies for individual and moderator-guided consensus reaching. The feasibility and applicability of the proposed method are demonstrated through an example analysis, highlighting its effectiveness and advantages.
INFORMATION FUSION
(2023)
Article
Computer Science, Artificial Intelligence
Guolin Tang, Xiaoyang Zhang, Baoying Zhu, Hamidreza Seiti, Francisco Chiclana, Peide Liu
Summary: This study presents an R-mathematical programming method for multiple attribute group decision-making problems with subjective bounded rationality. It proposes a novel scalar multiplication operation and defuzzification method for R-sets to be used in MAGDM. It also introduces a new technique based on prospect theory and R-sets to compute the individual overall prospect value of an alternative. The developed method estimates the decision makers' weights, attribute weights, positive ideal solution, and negative ideal solution using a novel R-mathematical programming model. The applicability, validity, and superiority of the method are verified through a practical instance and sensitive and comparative analyses.
INFORMATION FUSION
(2023)
Article
Computer Science, Artificial Intelligence
Yumei Xing, Jian Wu, Francisco Chiclana, Gaofeng Yu, Mingshuo Cao, Enrique Herrera-Viedma
Summary: A bargaining game is used to develop a feedback mechanism for dynamic social networks group decision making (SN-GDM). The trust relationships between experts are updated based on their consensus state after each round of interaction. A maximum entropy model is established to determine the comprehensive weight of each expert, considering both their influence and social relationships. The proposed feedback mechanism driven by trust relationship aims to promote consensus in SN-GDM by reflecting the interaction behaviors between inconsistent and trusted experts.
INFORMATION FUSION
(2023)
Article
Computer Science, Information Systems
Guolin Tang, Xiaowei Gu, Francisco Chiclana, Peide Liu, Kedong Yin
Summary: In this paper, a novel multi-objective q-ROF programming approach is proposed for heterogeneous multi-criteria group decision making (MCGDM) problems with incomplete weights and q-rung orthopair fuzzy (q-ROF) truth degrees. The approach captures the interactions among criteria by developing Choquet-based relative closeness degrees and defines q-ROF Choquet-based group consistency index (q-ROFCGCI) and q-ROF Choquet-based group inconsistency index (q-ROFCGII). A new multi-objective q-ROF mathematical programming model is established to derive optimal 2-additive fuzzy measures and experts' weights. The proposed approach is verified using four real cases concerning the evaluation of social commerce.
INFORMATION SCIENCES
(2023)
Article
Computer Science, Information Systems
Sheng-Hua Xiong, Chen-Ye Zhu, Zhen-Song Chen, Muhammet Deveci, Francisco Chiclana, Miroslaw J. Skibniewski
Summary: This study aims to expand the practical application scope of the power geometric operator and develop a proportional hesitant fuzzy linguistic large-scale group decision-making model. An extended power geometric (EPG) operator is introduced to identify outliers as important or false/biased data in accordance with the decision-making context. The study also proposes a proportional hesitant fuzzy linguistic extended power geometric (PHFLEPG) operator and provides a consensus reaching approach based on this operator to simplify the decision-making process. The feasibility and effectiveness of the established model are validated through a case study on regulatory capacity evaluation for the Civil Aviation Safety Regulatory Authority of China (CASRAC).
INFORMATION SCIENCES
(2023)
Article
Automation & Control Systems
Mengqi Li, Yejun Xu, Xia Liu, Francisco Chiclana, Francisco Herrera
Summary: Every decision involves risks, and real-world risk issues are usually supervised by third parties. This article presents a conflict-eliminating model based on trust risk analysis to manage trust risks in social network group decision making (SNGDM) through third-party monitoring. The model measures trust risk types and index, and provides management policies and optimization methods.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Automation & Control Systems
Hengjie Zhang, Shenghua Liu, Yucheng Dong, Francisco Chiclana, Enrique Enrique Herrera-Viedma
Summary: This study presents a framework called minimum cost consensus-based failure mode and effect analysis (MCC-FMEA) that considers experts' limited compromise and tolerance behaviors. It introduces two types of behaviors, limited compromise behavior and tolerance behavior, to the MCC-FMEA. The study develops and analyzes a minimum compromise adjustment consensus model and a maximum consensus model with limited compromise behaviors, resulting in an interactive MCC-FMEA framework.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Computer Science, Artificial Intelligence
Xinli You, Fujun Hou, Francisco Chiclana
Summary: This study aims to develop a reputation-based trust model for establishing trust relationships among experts in a group decision-making framework. The research achieves this by defining a trust credibility measure, designing direct trust feedback, and proposing a global reputation model.
INFORMATION FUSION
(2024)
