Special Issues
Table of Content

Algorithms, Models, and Applications of Fuzzy Optimization and Decision Making

Submission Deadline: 01 July 2025 View: 711 Submit to Special Issue

Guest Editors

Prof. Dr. Dragan Pamucar

Email: dragan.pamucar@fon.bg.ac.rs

Affiliation: Faculty of Organizational Sciences, University of Belgrade, Belgrade

Homepage:

Research Interests: Logistics & Transportation, Multiple Criteria Decision Making, Decision Support Systems, MCDM 

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Dr. Samayan Narayanamoorthy

Email: snmphd@buc.edu.in

Affiliation: Department of Mathematics, Bharathiar University, Coimbatore

Homepage:

Research Interests: Fuzzy Logic, Decision Sciences, MCDM, Differential  Equation, Industrial Engineering

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Dr. Daekook Kang

Email: dkkang@inje.ac.kr

Affiliation: Department of Industrial and Management Engineering, Inje University, Gimhae, 50834, South Korea

Homepage:

Research Interests: MCDM, Fuzzy set theory, Technology forecasting, Service engineering, Quality Management

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Summary

Fuzzy optimization is an approach that combines conventional techniques for optimization with fuzzy set theory in order to provide effective fuzzy optimization methods for both theoretical and practical application of solving problems in manufacturing, management, and artificial intelligence. Fuzzy decision-making is the act of making decisions using fuzzy logic, which permits a more adaptable interpretation of the available data.


The objective of this special issue is to advance different research and improvements in fuzzy technology and soft-computing methodologies to improve the capacity to handle complex optimization and decision-making problems involving imprecision, uncertainty, and incomplete information that can determine fuzzy optimal decisions and solutions. We welcome research articles pertaining to the state-of-the-art computation algorithms, mathematical models, theoretical advancements, systems developments, and applications. In order to help foster fuzzy technologies should be better understood, developed, and applied in engineering, management, and societal problems. The invitation for high-quality research papers and review articles on topics including, but not limited to:


Algorithms and methods for fuzzy optimization

Hybrid fuzzy optimization and data-driven techniques

Fuzzy multi-criteria decision making (FMCDM)

Integrating fuzzy with other soft computing methods

Advanced artificial intelligence based machine learning models

Large-scale group decision making

Extension of fuzzy sets, operations, and measures on uncertain information

Applications on environmental and financial impact assessment

Engineering control, optimization, and development

Allocating and scheduling resource using fuzzy logic

Risk analysis and financial planning

Optimization of supply chain and logistics


Keywords

Fuzzy sets and logic; Uncertain information; Advanced fuzzy systems; Uncertainty modelling; Fuzzy optimization; Multi-objective optimization; Engineering data analytics; AI in engineering management; Multi-criteria decision making; Fuzzy analytical hierarchy process; Sustainable development; Energy system; Supply chain management; Logistic specialist

Published Papers


  • Open Access

    ARTICLE

    Fuzzy N-Bipolar Soft Sets for Multi-Criteria Decision-Making: Theory and Application

    Sagvan Y. Musa, Baravan A. Asaad, Hanan Alohali, Zanyar A. Ameen, Mesfer H. Alqahtani
    CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2025.062524
    (This article belongs to the Special Issue: Algorithms, Models, and Applications of Fuzzy Optimization and Decision Making)
    Abstract This paper introduces fuzzy N-bipolar soft (FN-BS) sets, a novel mathematical framework designed to enhance multi-criteria decision-making (MCDM) processes under uncertainty. The study addresses a significant limitation in existing models by unifying fuzzy logic, the consideration of bipolarity, and the ability to evaluate attributes on a multinary scale. The specific contributions of the FN-BS framework include: (1) a formal definition and set-theoretic foundation, (2) the development of two innovative algorithms for solving decision-making (DM) problems, and (3) a comparative analysis demonstrating its superiority over established models. The proposed framework is applied to a real-world case More >

  • Open Access

    REVIEW

    Unveiling Effective Heuristic Strategies: A Review of Cross-Domain Heuristic Search Challenge Algorithms

    Mohamad Khairulamirin Md Razali, Masri Ayob, Abdul Hadi Abd Rahman, Razman Jarmin, Chian Yong Liu, Muhammad Maaya, Azarinah Izaham, Graham Kendall
    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1233-1288, 2025, DOI:10.32604/cmes.2025.060481
    (This article belongs to the Special Issue: Algorithms, Models, and Applications of Fuzzy Optimization and Decision Making)
    Abstract The Cross-domain Heuristic Search Challenge (CHeSC) is a competition focused on creating efficient search algorithms adaptable to diverse problem domains. Selection hyper-heuristics are a class of algorithms that dynamically choose heuristics during the search process. Numerous selection hyper-heuristics have different implementation strategies. However, comparisons between them are lacking in the literature, and previous works have not highlighted the beneficial and detrimental implementation methods of different components. The question is how to effectively employ them to produce an efficient search heuristic. Furthermore, the algorithms that competed in the inaugural CHeSC have not been collectively reviewed. This… More >

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