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Advances in Multiple-Criteria Decision Making: New Trends and Applications

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A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "D2: Operations Research and Fuzzy Decision Making".

Deadline for manuscript submissions: 30 May 2027 | Viewed by 8508

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Editors

Prof. Dr. Gabrijela Popovic

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Guest Editor

Faculty of Applied Management, Economics and Finance, University Business Academy in Novi Sad, Belgrade, Serbia
Interests: multiple-criteria decision-making; operational research; management
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Marko Mihić

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Guest Editor

Faculty of Organizational Sciences, University of Belgrade, Belgrade, Serbia
Interests: strategic project management; project portfolio management; strategic planning

Special Issue Information

Dear Colleagues,

We are pleased to announce a call for papers for a Special Issue, Advances in Multiple-Criteria Decision Making: New Trends and Applications. This Special Issue aims to showcase cutting-edge research on novel approaches, frameworks, and applications in multicriteria decision making (MCDM), reflecting the diverse and evolving landscape of decision making methodologies and their extensions in various domains. As real-world decision problems grow in complexity and scope, the MCDM methods become a cornerstone for developing frameworks and tools that support making structured, rational, and transparent decisions. With rapid advances in data availability, computational procedures, and algorithmic techniques, innovative MCDM approaches and methodologies continue to emerge, enhancing the ability to address increasingly complex problems with multiple, often conflicting criteria. This Special Issue seeks to capture these advancements by focusing on innovative theories, methodologies, and applications of MCDM. We encourage papers beyond traditional methodologies, incorporating emerging paradigms and exploring new applications and hybrid models that make MCDM more effective, accessible, and applicable to real-world challenges.

Prof. Dr. Gabrijela Popovic
Prof. Dr. Marko Mihić
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

advances in traditional MCDM methods
hybrid MCDM methods and models
developing new MCDM methods
introducing innovative extensions to the MCDM methods
applications of MCDM in industry and business
MCDM for policy and governance
MCDM in risk assessment and crisis management
sustainability and green MCDM applications
MCDM in emerging technologies

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Published Papers (5 papers)

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Research

37 pages, 1956 KB

Open AccessArticle

Comparative Assessment of Financial Market Development in African Economies: An Integrated MCDM Framework Based on CRISUS-LODECI-WENSLO Weighting and ARTASI Ranking

by Berrak Tekgün, Şerife Merve Koşaroğlu, Sarfaraz Hashemkhani Zolfani, Osman Yavuz Akbulut and Özcan Işık

Mathematics 2026, 14(10), 1677; https://doi.org/10.3390/math14101677 - 14 May 2026

Viewed by 485

Abstract

Financial market development is an inherently multidimensional construct shaped by institutional, legal, market-based, and macro-financial conditions, and therefore cannot be adequately captured through single-indicator proxies. To address this complexity, this research proposes an integrated hybrid multi-criteria decision-making methodology, namely the CRISUS (CRiterion Importance based on the SUm of Squares)-LODECI (LOgarithmic DEcomposition of Criteria Importance)-WENSLO (Weights by ENvelope and SLOpe)- ARTASI (Alternative Ranking Technique based on Adaptive Standardized Intervals) framework, to comparatively assess the financial market development performance of twenty-six African economies. The evaluation structure is grounded in six criteria derived from the Absa Africa Financial Markets Index, with decision matrix values computed as arithmetic averages over the 2022–2025 period to capture persistent structural characteristics rather than cyclical fluctuations. The three weighting procedures, each operating on mathematically distinct information extraction principles, are linearly integrated to yield a composite criterion weight vector that is robust to method-specific distributional assumptions. The resulting weights identify pension fund development, legal standards and enforceability, and market depth as the dominant criteria, collectively accounting for the preponderance of cross-country performance variation. ARTASI rankings place South Africa, Mauritius, and Namibia at the top of the performance distribution, while Madagascar, DRC, and Ethiopia occupy the lowest positions. Sensitivity analysis under alternative weighting parameterizations and benchmarking against seven established MCDM methods confirm the stability and convergent validity of the proposed framework. Full article

(This article belongs to the Special Issue Advances in Multiple-Criteria Decision Making: New Trends and Applications)

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21 pages, 586 KB

Open AccessArticle

Analysing Digital Government Performance Indicators Using a Clustering Technique-Embedded Fuzzy Decision-Making Framework

by Mehmet Erdem, Akın Özdemir, Hatice Yalman Kosunalp and Bozhana Stoycheva

Mathematics 2026, 14(7), 1233; https://doi.org/10.3390/math14071233 - 7 Apr 2026

Viewed by 820

Abstract

Digital transformation is reshaping societies by promoting the adoption of advanced technologies. Moreover, the digitization of public services has become an important focus for governments. In this paper, digital government performance indicators are analyzed to improve the efficiency of digitizing public services. Based on this awareness, the seven main criteria and twenty-one sub-criteria are determined. Then, a fuzzy decision-making framework is proposed to evaluate digital government performance across 165 countries as alternatives. To the best of our knowledge, limited studies have investigated an integrated clustering-based fuzzy decision-making framework for evaluating digital government performance. The intuitionistic trapezoidal fuzzy number-based analytical hierarchy process (ITFNAHP), a part of the introduced framework, is developed to find the weights of the main criteria and sub-criteria. Digital technologies, innovation, and the economy are the most significant criteria for digital government operations. The k-means clustering method is then employed to group the alternatives. The four clusters are obtained from the clustering technique. Next, the technique of order preference similarity to ideal solution (TOPSIS) is introduced to rank the digital governments of each cluster. Switzerland, Rwanda, North Macedonia, and Eswatini are the top choices among others in each cluster, respectively. Additionally, a sensitivity analysis is conducted considering the ten different situations. In addition, the managerial and policy implications are discussed, including the achievement of Sustainable Development Goals (SDGs). Full article

(This article belongs to the Special Issue Advances in Multiple-Criteria Decision Making: New Trends and Applications)

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27 pages, 1452 KB

Open AccessArticle

The Alternative Prioritization and Assessment System (ALPAS) Method for Environmental Performance Evaluation

by Alptekin Ulutaş, Ayşe Topal and Fatih Ecer

Mathematics 2025, 13(20), 3333; https://doi.org/10.3390/math13203333 - 20 Oct 2025

Cited by 10 | Viewed by 2147

Abstract

This study aims to evaluate the environmental performance of G7 countries using the Environmental Performance Index. To do this, we introduce a novel ranking multi-criteria method, Alternative Prioritization and Assessment System, for the first time in the literature. It offers a useful contribution to the multi-criteria decision-making field by tackling several ranking problems, such as low interpretability, a lack of dual evaluation metrics, and limited flexibility in data-driven scenarios. Moreover, three advanced multi-criteria decision-making weighting methods are used to assign weights to the environmental performance criteria. Therefore, the proposed Alternative Prioritization and Assessment System-based methodology evaluates the environmental performance of G7 countries in reaching sustainable development goals. The results show that the waste recovery rate is the paramount indicator, while unsafe drinking water has the least significance. Germany is ranked as the top-performing country, while Japan is ranked lowest. The key contribution of this research lies in the development and implementation of the Alternative Prioritization and Assessment System method, offering enhanced ranking stability, transparency, and dual-perspective evaluation. The use of the Environmental Performance Index further supports replicability and policy relevance. The proposed model can guide environmental policy formulation and benchmarking efforts among industrialized nations. It also provides a robust framework for cross-national sustainability comparisons in future research. Full article

(This article belongs to the Special Issue Advances in Multiple-Criteria Decision Making: New Trends and Applications)

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34 pages, 3002 KB

Open AccessArticle

A Refined Fuzzy MARCOS Approach with Quasi-D-Overlap Functions for Intuitive, Consistent, and Flexible Sensor Selection in IoT-Based Healthcare Systems

by Mahmut Baydaş, Safiye Turgay, Mert Kadem Ömeroğlu, Abdulkadir Aydin, Gıyasettin Baydaş, Željko Stević, Enes Emre Başar, Murat İnci and Mehmet Selçuk

Mathematics 2025, 13(15), 2530; https://doi.org/10.3390/math13152530 - 6 Aug 2025

Cited by 10 | Viewed by 2076

Abstract

Sensor selection in IoT-based smart healthcare systems is a complex fuzzy decision-making problem due to the presence of numerous uncertain and interdependent evaluation criteria. Traditional fuzzy multi-criteria decision-making (MCDM) approaches often assume independence among criteria and rely on aggregation operators that impose sharp transitions between preference levels. These assumptions can lead to decision outcomes with insufficient differentiation, limited discriminatory capacity, and potential issues in consistency and sensitivity. To overcome these limitations, this study proposes a novel fuzzy decision-making framework by integrating Quasi-D-Overlap functions into the fuzzy MARCOS (Measurement of Alternatives and Ranking According to Compromise Solution) method. Quasi-D-Overlap functions represent a generalized extension of classical overlap operators, capable of capturing partial overlaps and interdependencies among criteria while preserving essential mathematical properties such as associativity and boundedness. This integration enables a more intuitive, flexible, and semantically rich modeling of real-world fuzzy decision problems. In the context of real-time health monitoring, a case study is conducted using a hybrid edge–cloud architecture, involving sensor tasks such as heartrate monitoring and glucose level estimation. The results demonstrate that the proposed method provides greater stability, enhanced discrimination, and improved responsiveness to weight variations compared to traditional fuzzy MCDM techniques. Furthermore, it effectively supports decision-makers in identifying optimal sensor alternatives by balancing critical factors such as accuracy, energy consumption, latency, and error tolerance. Overall, the study fills a significant methodological gap in fuzzy MCDM literature and introduces a robust fuzzy aggregation strategy that facilitates interpretable, consistent, and reliable decision making in dynamic and uncertain healthcare environments. Full article

(This article belongs to the Special Issue Advances in Multiple-Criteria Decision Making: New Trends and Applications)

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28 pages, 5989 KB

Open AccessArticle

Application of Soft Computing Techniques in the Analysis of Educational Data Using Fuzzy Logic

by Marija Mojsilović, Selver Pepić, Gabrijela Popović, Muzafer Saračević and Darjan Karabašević

Mathematics 2025, 13(13), 2096; https://doi.org/10.3390/math13132096 - 26 Jun 2025

Cited by 1 | Viewed by 1253

Abstract

The application of soft computing techniques, with a special emphasis on fuzzy logic, represents a modern approach to analyzing complex educational data. This paper explores the possibilities of applying soft computing to identify and interpret factors that influence the motivation and educational achievement of students in academic and professional studies, with special reference to the differences between these two groups of students in experienced subjects. Fuzzy logic enables more detailed processing of educational parameters that are subject to subjective interpretations and are often not clearly defined. By using this approach, decision support systems are developed that facilitate the understanding of students’ motivational patterns, their preferences, and challenges in mastering different types of content. Analyzing educational data seeks to identify relevant motivational factors that can contribute to shaping more effective and personalized teaching strategies. The goal of the work is to improve the quality of the educational process through the integration of soft computing methods, to raise the level of engagement and success of students in various fields of study. Full article

(This article belongs to the Special Issue Advances in Multiple-Criteria Decision Making: New Trends and Applications)

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