Research on Fuzzy Sets and Multi-Criteria Decision Making with Applications

A special issue of Axioms (ISSN 2075-1680). This special issue belongs to the section "Mathematical Analysis".

Deadline for manuscript submissions: 25 December 2026 | Viewed by 955

Special Issue Editors


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Guest Editor
Department of Information Management, Chaoyang University of Technology, Taichung 41349, Taiwan
Interests: fuzzy logic; sustainability; technology adoption; service quality; multi-criteria decision support networks; data mining
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Guest Editor
Faculty of Mining and Geology, University of Belgrade, Đušina 7, 11000 Belgrade, Serbia
Interests: multicriteria analysis; decision making; fuzzy set theory; uncertainty analysis; forecasting; linear programming; k-means; clustering; clustering algorithms; simulation; stochastic system theory

Special Issue Information

Dear Colleagues,

This Special Issue focuses on advancing theoretical and applied research in fuzzy sets, rough set theory, and uncertainty modeling for improving decision quality in complex, real-world environments. In the era of data-driven innovation, organizations increasingly rely on Multi-Criteria Decision Making (MCDM) and decision making theory to handle ambiguity, conflicting objectives, and dynamic system interactions. The integration of fuzzy and rough set-based approaches provides robust analytical tools for dealing with incomplete, imprecise, and uncertain information, enabling more accurate and transparent evaluations.

The Special Issue welcomes contributions that develop or apply Decision Support Systems (DSS) and hybrid MCDM frameworks for optimizing outcomes in diverse domains, particularly business management, technology adoption, and sustainable process design. Studies addressing the intersection of mathematical modeling, intelligent computing, and sustainability-driven strategies are especially encouraged. Potential topics include novel MCDM models, fuzzy–rough hybrid systems, risk analysis under uncertainty, and decision support methodologies for digital transformation and sustainable development. By combining theoretical rigor with practical relevance, this Special Issue aims to contribute to the evolution of intelligent decision making systems that support responsible innovation and sustainable progress.

Dr. Venkateswarlu Nalluri
Dr. Miloš Gligorić
Guest Editors

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Keywords

  • fuzzy sets
  • rough set theory
  • uncertainty modeling
  • multi-criteria decision making
  • decision making theory
  • decision support system
  • modeling in business management
  • technology adoption
  • sustainable processes MCDM

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Published Papers (1 paper)

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Research

36 pages, 3930 KB  
Article
Optimization Consensus Model Considering Minimum Cost and Maximum Consensus Objectives for Social Network Group Decision-Making
by Shuping Zhao, Xue Jiang and Wenxing Lu
Axioms 2026, 15(4), 245; https://doi.org/10.3390/axioms15040245 - 25 Mar 2026
Viewed by 493
Abstract
In social network-based group decision-making, achieving consensus often entails costs, leading to an inherent trade-off between cost and consensus. To address this issue, we propose a dual-semantic, multi-objective consensus optimization model that simultaneously minimizes cost and maximizes consensus. The resulting Pareto set offers [...] Read more.
In social network-based group decision-making, achieving consensus often entails costs, leading to an inherent trade-off between cost and consensus. To address this issue, we propose a dual-semantic, multi-objective consensus optimization model that simultaneously minimizes cost and maximizes consensus. The resulting Pareto set offers decision makers (DMs) multiple trade-off solutions between cost and consensus. Specifically, we first develop a 2-tuple trust propagation model that incorporates path knowledge and path length to improve the completeness and accuracy of indirect trust inference. Building on this foundation, we adaptively adjust DM weights by combining trust relationships with dynamic incentive weights. This design balances individual influence and adjustment willingness throughout the consensus-reaching process. Finally, we formulate a multi-objective decision optimization model. This model integrates minimum cost and maximum consensus to generate a modified decision matrix for efficiently aggregating group opinions. A multi-physician collaboration case in a medical diagnostic decision-support system validates the effectiveness of the proposed method. Full article
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