Spectrum of Operational Research
type: channel
description: Spectrum of Operational Research focuses on advancing operational research, management science and analytics through theoretical insights, developments and real-world case studies. The material published is of high quality and relevance, written in a manner that makes it accessible to this wide-ranging readership. Spectrum of Operational Research is an international peer-reviewed journal covering the main aspects of operational research and analytics and providing a source of information for applied scientists. The journal explores interactions of operational research, management science, and analytics with other relevant disciplines. Spectrum of Operational Research aims at this important task by providing a venue for high-quality scientific papers that contribute significantly to the field of operational research, management science and analytics. The material published is of high quality and relevance, written in a manner that makes it accessible to a wide-ranging readership. Papers reporting original theoretical and/or practice-oriented research or extended versions of the already published conference papers are all welcome. The scope of the journal covers the whole spectrum of decision science. Papers for publication are selected through a double-blind peer-review process to ensure originality, relevance, and readability. In doing that, the objective is not only to keep the quality of published papers high but also to provide a timely, thorough, and balanced review process. General Journal guidelines for authors Spectrum of Operational Research publishes research articles, reviews, short communications, and case studies. Research articles must include: motivation for the work, an adequate overview of the representative work in the field including up-to-date references, a clear statement of the novelty in the presented research, suitable theoretical background, one or more examples to demonstrate and discuss the presented ideas and, finally, conclusions. Short c…
publisher: Scientific Oasis
language: en
publication name: Spectrum of Operational Research
issn: 3042-1470
items: A Systematic Review of integrated GIS and MCDM methodology for Wind Farm Site Selection: Trends, Methods, and Criteria
items: Quantifying Multi-Cause Psychological Disorder Risk Through an Advanced Mathematical Model Using Intuitionistic Pentagonal Fuzzy Logic
items: Prioritizing MSMEs based on technology adoption capabilities: A fuzzy SAW-COPRAS approach
items: Sustainable Urban Development: q-Rung Orthopair Fuzzy MCDM with Generalized Power Prioritized Yager Aggregation
items: Research on the Redefined Square Root Interval-valued Normal Pythagorean Fuzzy Multi-Attribute Decision-Making Model Based on Aggregation Operators
items: Stochastic Models for Autonomous Systems and Robotics
items: Sustainable Supplier Selection Based on a Comparative Decision-Making Approach Under Uncertainty
items: A Study for Application of Decision Making Model in a Public Organization
items: Analysis of Innovation Performance of South- Eastern European Countries in Transition Economies: An Application of the Entropy-Based ARTASI Method
items: Investigation of Threats to Data States in Data Loss Prevention Using the Concept of Complex Linear Diophantine Fuzzy Relations
items: Enhancing Web Security Through Complex Cubic q-Rung Orthopair Fuzzy Information
items: Evaluation of Purchasing Process in Solar Energy Investment Projects via SIWEC Methodology
items: Interpretable Robust Multicriteria Ranking with TODIM in Generalized Orthopair Fuzzy Settings
items: Fundamental Characteristics and Applicability of the RADAR Method: Proof of Ranking Consistency
items: A Study on DEMATEL Approach Under Uncertainty Environments
items: Sustainable Urban Transportation: Key Criteria for a Greener Future
items: Fuzzy SIWEC and Fuzzy RAWEC Methods for Sustainable Waste Disposal Technology Selection
items: Shadowed Offset: Integrating Offset and Shadowed Set Frameworks for Enhanced Uncertainty Modeling
items: Decision-Making Framework for Urban Transportation Using Linear Diophantine Fuzzy Z-numbers with Dombi Aggregation, TOPSIS and VIKOR Methods
items: Remote Sensing-Based Evaluation of Lake Area Dynamics: A Quantitative Assessment for Environmental Management in Turkey
items: Solution of Fuzzy System of Linear Equation Under Different Fuzzy Difference Ideology
items: A Decision-Making Framework for Sustainable Highway Restaurant Site Selection: AHP-TOPSIS Approach based on the Fuzzy Numbers
items: On the Anticancer Drug Structures and Their Locating Numbers
items: Optimizing Vendor-Managed Inventory in Multi-Tier Distribution Systems
items: A Framework for Extensive Content-Based Image Retrieval System Incorporating Relevance Feedback and Query Suggestion
items: Best Practice Performance of COVID-19 in America continent with Artificial Intelligence
items: Parametric Analysis and ANN Prediction of Biogas Yield from Anaerobic Biochemical Reactions of Non-Uniform Organic Substrates under Mesophilic Regime
items: An Expert Opinion-Based Soft Computing Framework for Comparing Nanotechnologies used in Agriculture
items: Review of Probabilistic HyperGraph and Probabilistic SuperHyperGraph
items: Multi-Criteria Evaluation of Wind Turbines using Entropy-based-TOPSIS and CoCoSo Methods: Insights from a Turkish Case Study

A Systematic Review of integrated GIS and MCDM methodology for Wind Farm Site Selection: Trends, Methods, and Criteria
type: item
description: Wind energy has emerged as one of the most promising renewable energy sources and a sustainable alternative to conventional fossil fuels. However, selecting suitable locations for wind farms is a complex process that depends on several factors, including social, technological, economic, and environmental aspects. Over the past decade, academics have increasingly employed combinations of Geographic Information Systems (GIS) and Multi-Criteria Decision-Making (MCDM) techniques to address the challenges of wind farm location selection. This tendency is reflected in the significant number of scholarly papers on the subject. To give researchers a state-of-the-art perspective and a thorough understanding of current approaches, a comprehensive review of 147 studies published between 2015 and 2025 was carried out. A constructed taxonomy that encompasses GIS software, application fields, uncertainty treatment, MCDM techniques, spatial resolution in GIS, and site selection criteria was used to classify the examined studies. The most popular MCDM techniques for criterion weighting and ranking of alternatives are the Analytical Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. An examination of the criteria reveals that wind speed, slope, land use, distance from transmission lines, road proximity, environmental restrictions, and social acceptance are the most frequently considered factors during wind farm site selection. Identifying research gaps, improving modelling techniques, and facilitating well-informed decision-making in future wind energy development initiatives are all made possible by these classifications and insights.
subject: Articles
  topic: section
subject: Multi-criteria decision-making
  topic: keywords
subject: MCDM
  topic: keywords
subject: Geographic information system
  topic: keywords
subject: GIS
  topic: keywords
subject: Wind energy
  topic: keywords
subject: Renewable energy
  topic: keywords
creator: Emhemed Algazel
creator: Ibrahim Badi
rights: Copyright (c) 2026 Emhemed Algazel, Ibrahim Badi (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-03
publication date: 2026-01-03
starting page: 1
ending page: 19
doi: 10.31181/sor41202761

Quantifying Multi-Cause Psychological Disorder Risk Through an Advanced Mathematical Model Using Intuitionistic Pentagonal Fuzzy Logic
type: item
description: The evaluation of psychological disorders is a very complicated and sensitive area of study, where emotions, thoughts, and the mental states of different patients are analyzed on the basis of questionnaires and observational techniques. The identification and analysis of people's mental states, emotions, and behaviors are difficult and limited with the aid of conventional approaches since the data gathered from these factors appear to be vague, uncertain, and imprecise. To demonstrate this information systematically, we have proposed a comprehensive mathematical model able to deal with indeterminate and imprecise data, utilizing Intuitionistic Pentagonal Fuzzy Numbers (IPnFNs). To create a coherent mathematical framework, IPnFNs integrate five values of membership and non-membership functions of any constraint, providing an innovative numerical framework that effectively explains the assessment of diagnosis and the patient's condition. The research study analyzes several key psychiatric disorders, such as childhood psychiatric problems, hormonal changes, social stress, cognitive distortions, anxiety, and traumatic life events, as the main factors. The proposed technique provides psychologists with a thorough and clear picture of the issue by depicting the patient's mental health numerically. The research is significantly helpful in cases where the symptoms of psychological illness are not obvious or the patient's information is imprecise or confusing. Furthermore, a comparative analysis of various patients can be developed using the proposed technique, assisting in assessing severity and diagnosis preferences. This mathematical method shows that the use of IPnFNs can be a reliable and scientific method in the evaluation of psychological disorders. This approach is significantly applicable in educational counseling and clinical psychology, where it is a daily routine for individuals to deal with imprecise and inconsistent data in mental health issues while making dec…
subject: Articles
  topic: section
subject: Multi-Criteria Decision Making
  topic: keywords
subject: Intuitionistic Pentagonal Fuzzy Framework
  topic: keywords
subject: Fuzzy Logical operators
  topic: keywords
subject: Psychiatric Disorder Evaluation
  topic: keywords
creator: Aiman Ishtiaq
creator: Khadija Tul Kubra
creator: Anns Uzair
creator: Awais Ali
rights: Copyright (c) 2025 Aiman Ishtiaq, Khadija Tul Kubra, Anns Uzair, Awais Ali (Author) https://creativecommons.org/licenses/by/4.0
date: 2025-11-03
publication date: 2025-11-03
starting page: 1
ending page: 21
doi: 10.31181/sor41202762

Prioritizing MSMEs based on technology adoption capabilities: A fuzzy SAW-COPRAS approach
type: item
description: Emerging economies have started focusing on micro, small, and medium enterprises (MSMEs) as they see a lot of potential in these businesses. Quite often, these sectors are unorganized, but there is a significant contribution to the economy from them. Industry 4.0 has emphasized automation and encouraged the use of technologies. In this context, upskilling and reskilling are required. At the ground level, such technological adoptions are not direct, and the implementation of such technologies incurs challenges that affect the process of adoption. This paper presents a combined decision approach for the prioritization of MSMEs based on technology adoption capabilities. It must be noted that the presented framework attempts to prioritize MSMEs based on their ability to handle technology adoption issues. Notably, every MSME undergoes a transition in social, economic, and environmental contexts when shifting to technology-driven solutions. To facilitate the process and aid in better understanding, this paper puts forward a combined decision approach. First, the technology adoption factors are presented based on a literature review and discussions with MSME stakeholders. Later, Fuzzy SAW is used to determine the weights of tech-adoption criteria. These weights signify the relative importance of each criterion. Likewise, Fuzzy COPRAS is used to assign priority values to MSMEs. We consider the simple and straightforward procedure along with its ability to understand the criteria type before making a decision. Implications are discussed to support policymakers. A case example from India is considered to determine the usefulness of the proposed model. The results indicate that the top three criteria are lack of skillset (T5), infrastructure mismatch (T6), and high initial cost (T7), which are used to prioritize MSMEs.
subject: Articles
  topic: section
subject: Technology adoption
  topic: keywords
subject: COPRAS
  topic: keywords
subject: MCDM
  topic: keywords
subject: Industry 4.0
  topic: keywords
subject: Sustainability
  topic: keywords
creator: Kattur Soundarapandian Ravichandran
creator: Durga Nandhini
rights: Copyright (c) 2025 Kattur Soundarapandian Ravichandran, Durga Nandhini (Author) https://creativecommons.org/licenses/by/4.0
date: 2025-10-27
publication date: 2025-10-27
starting page: 1
ending page: 7
doi: 10.31181/sor41202754

Sustainable Urban Development: q-Rung Orthopair Fuzzy MCDM with Generalized Power Prioritized Yager Aggregation
type: item
description: In light of accelerating urbanization and the intensifying challenges of climate change, ensuring sustainability and resilience in urban environments has become a strategic imperative. This study introduces an innovative methodology that combines Multi-Criteria Decision Making (MCDM) with q-rung orthopair fuzzy Yager aggregation operators (q-ROFYAOs) to address the multifaceted complexities of sustainable urban development. The paper proposes novel Yager operations grounded in Yager t-norms within the framework of q-rung orthopair fuzzy sets (q-ROFSs). Utilizing these foundations, two advanced aggregation operators are formulated: the q-Rung Orthopair Fuzzy Generalized Power Prioritized Yager Weighted Average Operator (q-ROFGPOPRYWA) and the q-Rung Orthopair Fuzzy Generalized Power Prioritized Yager Weighted Geometric Operator (q-ROFGPOPRYWG). These operators satisfy essential mathematical properties, including idempotency, monotonicity, and boundedness, ensuring consistency and reliability in decision-making contexts. To demonstrate the practical relevance of the proposed approach, the operators are embedded within an MCDM framework and applied to a real-world case study on sustainable urban planning. The analysis encompasses sensitivity testing, comparative evaluations, and performance assessments, offering comprehensive insights into the robustness of the method. Finally, the paper provides a critical evaluation of the advantages and limitations of the proposed operators, underscoring their effectiveness in promoting urban resilience and minimizing environmental impact within complex decision-making environments.
subject: Articles
  topic: section
subject: Sustainable Urban Development
  topic: keywords
subject: Multi-Criteria Decision Making
  topic: keywords
subject: q-Rung Orthopair Fuzzy Sets
  topic: keywords
subject: Yager Aggregation Operators
  topic: keywords
subject: Power Prioritized Aggregation
  topic: keywords
creator: Subramanian Petchimuthu
creator: Balakrishnan Palpandi
creator: K Rajakumar
creator: Fathima Banu M
rights: Copyright (c) 2026 Subramanian Petchimuthu, Balakrishnan Palpandi, K Rajakumar, Fathima Banu M (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-01
publication date: 2026-01-01
starting page: 275
ending page: 309
doi: 10.31181/sor31202649

Research on the Redefined Square Root Interval-valued Normal Pythagorean Fuzzy Multi-Attribute Decision-Making Model Based on Aggregation Operators
type: item
description: In this paper, we construct new multiple attribute decision-making (MADM) problems using the redefined square root interval-valued normal Pythagorean fuzzy set (RSIVNPFS). The interval-valued Pythagorean fuzzy sets (IVPFSs) and square root PFSs are extended by the square RSIVNPFS. We introduce RSIVNPF weighted averaging (RSIVNPFWA), RSIVNPF weighted geometric (RSIVNPFWG), generalized RSIVNPFWA (RSGIVNPFWA), and generalized RSIVNPFWG (RSGIVNPFWG). Idempotence, boundedness, commutativity, and monotonicity in algebraic operations are all satisfied by RSIVNPFSs. We develop an algorithm for dealing with MADM problems using the aggregation operators (AOs). The applications of the Euclidean distance (ED) and the Hamming distance (HD) are described using examples from everyday scenarios. We also compare several suggested and current models to show the validity and applicability of the models. Our objective is to compare expert opinions with the criteria in order to determine the best option and to demonstrate the superiority and validity of the suggested AOs.
subject: Articles
  topic: section
subject: Multiple attributes decision-making
  topic: keywords
subject: Aggregating operations
  topic: keywords
subject: Normal fuzzy set
  topic: keywords
subject: Weighted vector
  topic: keywords
subject: Weighted averaging
  topic: keywords
subject: Weighted geometric
  topic: keywords
creator: Murugan Palanikumar
creator: Nasreen Kausar
rights: Copyright (c) 2025 Murugan Palanikumar, Nasreen Kausar (Author) https://creativecommons.org/licenses/by/4.0
date: 2025-08-21
publication date: 2025-08-21
starting page: 1
ending page: 18
doi: 10.31181/sor58

Stochastic Models for Autonomous Systems and Robotics
type: item
description: The field of robotics is rapidly evolving with the development of autonomous systems capable of operating in dynamic and uncertain environments. A key challenge is ensuring that these systems can reliably make decisions and execute tasks despite inherent uncertainties. Stochastic modeling provides a crucial mathematical framework to address these uncertainties by incorporating randomness and variability in system behavior and external conditions. This paper explores the role of stochastic models in autonomous systems, particularly in navigation, decision-making, and task execution, and how they integrate with artificial intelligence and machine learning to enhance system robustness and adaptability. A case study on autonomous vehicles (AVs) demonstrates the application of stochastic models, highlighting the use of Markov Decision Processes (MDPs) for path planning, Kalman filters for sensor fusion, and Monte Carlo methods for probabilistic localization. Through detailed mathematical and computational analyses, we show how these stochastic methods help AVs navigate uncertain urban environments, improving decision-making and overall system performance.
subject: Articles
  topic: section
subject: Stochastic Modeling
  topic: keywords
subject: Autonomous Systems
  topic: keywords
subject: Decision-Making
  topic: keywords
subject: Navigation
  topic: keywords
subject: Kalman Filters
  topic: keywords
subject: Monte Carlo Localization
  topic: keywords
creator: Shankha Shubhra Goswami
creator: Surajit Mondal
rights: Copyright (c) 2026 Shankha Shubhra Goswami, Surajit Mondal (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-01
publication date: 2026-01-01
starting page: 215
ending page: 237
doi: 10.31181/sor31202647

Sustainable Supplier Selection Based on a Comparative Decision-Making Approach Under Uncertainty
type: item
description: Nowadays, due to the increasing awareness of sustainability and green issues worldwide, companies are forced to implement sustainable projects in their supply chain (SC) to maintain and increase their competitive advantage. To enhance business performance and gain a competitive edge, it is crucial to select green and sustainable suppliers in the supply chain, as they play a vital role in executing sustainable projects. Therefore, this research was conducted to select sustainable suppliers in the SC. Initially, a list of indicators for selecting sustainable suppliers was extracted, and these indicators were adjusted and finalized using the fuzzy Delphi technique. Also, the Step-wise Weight Assessment Ratio Analysis (SWARA) technique was used for weighting, and the Fuzzy Weighted Aggregates Sum-Product Assessment (F-WASPAS) technique was used for prioritizing suppliers. In addition, the robustness of the findings was examined using a comparative analysis of different decision methods in a fuzzy environment. The weighting results showed that the product price, transportation cost, and green design and purchasing indicators were of the highest importance, respectively. Moreover, the results of the supplier ranking revealed that the first supplier had the highest priority.
subject: Articles
  topic: section
subject: Supplier selection
  topic: keywords
subject: Fuzzy Delphi
  topic: keywords
subject: Multi-criteria decision-making
  topic: keywords
subject: MCDM
  topic: keywords
subject: Comparative analysis
  topic: keywords
subject: Fuzzy numbers
  topic: keywords
subject: Sustainable development
  topic: keywords
creator: Seyyed Jalaladdin Hosseini Dehshiri
rights: Copyright (c) 2026 Seyyed Jalaladdin Hosseini Dehshiri (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-01
publication date: 2026-01-01
starting page: 238
ending page: 251
doi: 10.31181/sor31202644

A Study for Application of Decision Making Model in a Public Organization
type: item
description: Decision-making can be regarded as an outcome of mental processes leading to the selection of a course of action among numbers of alternatives available at a point of time. Each decision making process produces a final choice and the output will be an action or an opinion of choice (Decision Making). Decision making is, however, only a step in planning, even when it is taken quickly, with little thoughts and information or when it effects action for few minutes only. Everyone takes decision daily in his life for every course of action. Seldom there is a chance to judge a course of action in isolation, as every decision has to gear up other plans. In public organization consensus can be a goal, not a mandate for public decision-making. Public policies are the mixture of our values and opinions, technical knowledge and abilities, and political set up. These are the views often conflict with one another, but when they differ from the individual views, generate disregard for the opinions and perspectives of others.
subject: Articles
  topic: section
subject: Decision- making
  topic: keywords
subject: Public organization
  topic: keywords
subject: Alternatives
  topic: keywords
subject: Technical knowledge
  topic: keywords
subject: Opinion
  topic: keywords
creator: Divanshu Mittal
rights: Copyright (c) 2026 Divanshu Mittal (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-01
publication date: 2026-01-01
starting page: 183
ending page: 192
doi: 10.31181/sor31202640

Analysis of Innovation Performance of South- Eastern European Countries in Transition Economies: An Application of the Entropy-Based ARTASI Method
type: item
description: Innovation performance has emerged as a crucial policy concern for nations undergoing institutional change and economic restructuring. Using a novel hybrid multi-criteria decision-making (MCDM) framework, this study assesses the innovation capacities of five transition economies in South-Eastern Europe: Albania, Bosnia and Herzegovina, Montenegro, North Macedonia, and Serbia. Although the Global Innovation Index (GII) is widely regarded as a comprehensive benchmarking tool, its aggregated scoring system often obscures contextual subtleties, particularly in smaller or less-studied economies. To address these limitations, this study combines the ARTASI ranking model with objective weighting methods—Entropy and CRITIC—providing a transparent, flexible, and reproducible evaluation framework. The results indicate that output-oriented indicators—such as Knowledge and Technology Outputs, Market Sophistication, and Creative Outputs—are the most significant factors in differentiating national innovation performance. Among the analyzed countries, Serbia leads the regional ranking, followed by North Macedonia and Montenegro, while Albania and Bosnia and Herzegovina exhibit notable output-related deficiencies. Robustness checks—including sensitivity analysis and cross-validation with alternative MCDM techniques—confirm the model's stability and reliability. Beyond addressing a geographic gap in the innovation literature, this study offers a methodologically refined approach to innovation evaluation. The proposed framework can serve as a foundation for comparative research in similar socioeconomic contexts and guide evidence-based policymaking in transition economies.
subject: Articles
  topic: section
subject: Innovation Performance
  topic: keywords
subject: Global Innovation Index (GII)
  topic: keywords
subject: South-Eastern European Countries
  topic: keywords
subject: Transition Economies
  topic: keywords
subject: Multi-Criteria Decision Making (MCDM)
  topic: keywords
subject: Entropy
  topic: keywords
subject: ARTASI
  topic: keywords
creator: Gökhan Çobanoğulları
creator: Kübra Daldıran
creator: Bünyamin Daldıran
rights: Copyright (c) 2026 Gökhan Çobanoğulları, Kübra Daldiran, Bünyamin Daldiran (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-01
publication date: 2026-01-01
starting page: 193
ending page: 214
doi: 10.31181/sor31202642

Investigation of Threats to Data States in Data Loss Prevention Using the Concept of Complex Linear Diophantine Fuzzy Relations
type: item
description: In today's digital age, many operational decisions in businesses rely on data sources, enabling organizations to enhance productivity, make informed decisions, and gain competitive advantages. However, businesses also face data breaches involving sensitive information—such as financial records, intellectual property, and customer personal data—which may be compromised inadvertently. These threats can often be mitigated by implementing robust cybersecurity measures, such as Data Loss Prevention (DLP), to ensure proper monitoring and control of all organizational data, enforce policies without exceptions, and prevent unauthorized data transfers or rule violations. Despite these measures, uncertainties remain regarding the efficacy of identifying threats at various stages of data loss to mitigate their adverse effects through effective cybersecurity. To address this, this paper introduces Complex Linear Diophantine Fuzzy Relations (CLDFRs). For the first time in fuzzy set theory, we analysed the relationships between various threats and components of DLP-based data loss solutions. Additionally, we present the concept of Hasse diagrams for Complex Linear Diophantine Fuzzy Sets and Relations to examine different cybersecurity methods and procedures. This approach helps determine the most effective strategy based on Hasse diagram analysis. Furthermore, after applying specific constraints to the decision-making process, the optimal cybersecurity approach is selected. Finally, a comparative analysis demonstrates the advantages of the proposed methods.
subject: Articles
  topic: section
subject: Complex Linear Diophantine Fuzzy Relation
  topic: keywords
subject: Complex Linear Diophantine Fuzzy Set
  topic: keywords
subject: Data Loss Prevention
  topic: keywords
subject: Data Security
  topic: keywords
creator: Sami Ullah Khan
creator: Abdul Nasir
creator: Malaika Marwat
rights: Copyright (c) 2026 Sami Ullah Khan, Abdul Nasir, Malaika Marwat (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-01
publication date: 2026-01-01
starting page: 128
ending page: 152
doi: 10.31181/sor31202638

Enhancing Web Security Through Complex Cubic q-Rung Orthopair Fuzzy Information
type: item
description: Over the past two decades, the evolution of web services has profoundly transformed communication and information technologies. As computer programs that facilitate data exchange and interoperability between applications via the Internet, web services play a pivotal role in enabling seamless interactions and information access. However, despite their advantages, these platforms also introduce significant security risks. This study leverages the novel framework of Complex Cubic q-Rung Orthopair Fuzzy Sets (CCuqROFS) to model and address these security threats effectively. Unlike conventional models, CCuqROFS provides a robust structure that incorporates membership (M) and non-membership (NM) degrees, offering a more precise representation of uncertainty. Through illustrative examples, we introduce key concepts such as Complex Cubic q-Rung Orthopair Fuzzy Relations (CCuqROFR), the Cartesian product of CCuqROFSs, and various forms of CCuqROFRs. For the first time in fuzzy set theory, this work systematically examines the relationships between different security threats and countermeasures in web services. The proposed methodologies demonstrate how robust security measures can mitigate the impact of these threats. Finally, a comparative analysis underscores the advantages of our strategies, providing valuable insights for enhancing web service security.
subject: Articles
  topic: section
subject: Web services
  topic: keywords
subject: Complex cubic q-rung orthopair fuzzy set
  topic: keywords
subject: Complex cubic q-rung orthopair fuzzy relations
  topic: keywords
creator: Shoukat Hussain
rights: Copyright (c) 2026 Shoukat Hussain (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-01
publication date: 2026-01-01
starting page: 153
ending page: 182
doi: 10.31181/sor31202641

Evaluation of Purchasing Process in Solar Energy Investment Projects via SIWEC Methodology
type: item
description: Solar energy investments involve financial and technological commitments aimed at generating electricity or heat from sunlight. Direct electricity production is achieved through solar panels, while concentrated sunlight produces high-temperature energy. The importance of solar energy investments can be assessed from multiple perspectives. These projects reduce carbon emissions by decreasing reliance on fossil fuels. Solar energy investments are becoming increasingly vital, particularly in alignment with energy transition and sustainable development goals. In short, solar energy is a sustainable and environmentally friendly power source. It also enhances energy access in rural areas through off-grid energy production. To identify the critical factors influencing procurement performance in solar energy investments, a novel decision-making model is proposed, incorporating the SIWEC technique. The findings reveal that strategy definition is the most crucial aspect of the procurement process in solar energy investments. A common digital platform should be implemented across all company units to improve coordination in project and procurement processes. This platform enables real-time tracking of business plans, ensuring timely service delivery and more effective project risk management. Additionally, robust project management software should be utilized to monitor all stages of solar energy projects. Such tools help streamline supply processes, meet material requirements on time, and optimize costs. Potential disruptions in project planning can be identified early through digital systems, further reducing operational expenses. A transparent, data-driven supplier evaluation and selection process should be established to identify the most suitable suppliers for solar energy investments. Supplier performance must be monitored, evaluated, and reviewed periodically. Selecting the right supplier enhances project quality and overall efficiency.
subject: Articles
  topic: section
subject: Solar Energy
  topic: keywords
subject: Energy Investments
  topic: keywords
subject: Purchasing Process
  topic: keywords
subject: SIWEC
  topic: keywords
creator: Enes Şimşek
creator: Serkan Eti
creator: Serhat Yüksel
creator: Hasan Dinçer
rights: Copyright (c) 2026 Enes Şimşek, Serkan Eti, Serhat Yüksel, Hasan Dinçer (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-01
publication date: 2026-01-01
starting page: 81
ending page: 86
doi: 10.31181/sor31202636

Interpretable Robust Multicriteria Ranking with TODIM in Generalized Orthopair Fuzzy Settings
type: item
description: The endeavor to align TODIM (an acronym in Portuguese for interactive and multicriteria decision making) with prospect theory has given rise to the development of several variant methods, including power TODIM, exponential TODIM, and logarithmic TODIM. However, these existing methods fail to address high-order uncertainty within generalized orthopair fuzzy environments. To overcome this limitation, we propose an interpretable robust TODIM approach tailored for generalized orthopair fuzzy settings. First, we extend these TODIM methods to accommodate generalized orthopair fuzzy settings, integrating them into a unified framework. Second, we introduce a set of robustness analysis measures for the extended TODIM method, accounting for simultaneous uncertainty in criteria weights, value function coefficients, and the membership and non-membership degrees of generalized orthopair fuzzy sets. Third, we develop a programming model to determine representative criteria weights based on these robustness analysis measures, followed by an approach to recommend an interpretable and robust ranking within the extended TODIM framework. Finally, we present an illustrative example to demonstrate the application of this interpretable and robust TODIM approach, accompanied by a comparative analysis to highlight its advantages.
subject: Articles
  topic: section
subject: TODIM
  topic: keywords
subject: q-rung orthopair fuzzy sets
  topic: keywords
subject: Robustness analysis
  topic: keywords
subject: Interpretability
  topic: keywords
subject: Prospect theory
  topic: keywords
creator: Wenkai Zhang
creator: Hengxia Gao
rights: Copyright (c) 2026 Wenkai Zhang, Hengxia Gao (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-01
publication date: 2026-01-01
starting page: 14
ending page: 28
doi: 10.31181/sor31202632

Fundamental Characteristics and Applicability of the RADAR Method: Proof of Ranking Consistency
type: item
description: This paper presents a mathematical explanation of one of the Multi-Attribute Decision-Making (MADM) methods—the Ranking based on Distance and Range (RADAR) method—along with its modified variant, RADAR II. Through mathematical proofs, the influence of each step of the method on the final ranking of alternatives is analyzed. The methods are tested on three numerical examples with varying criterion weights. The robustness of the methods, as well as their fundamental characteristics, is demonstrated. A comparative analysis reveals that although both methods prioritize alternatives based on their stability across all criteria—particularly the most important ones—the RADAR II method is somewhat more rigorous and stringent, whereas the original RADAR method is more flexible and yields more objective results.
subject: Articles
  topic: section
subject: MADM
  topic: keywords
subject: RADAR
  topic: keywords
subject: RADAR II
  topic: keywords
subject: Mathematical proofs
  topic: keywords
subject: Fundamental characteristics
  topic: keywords
creator: Nikola Komatina
creator: Dragan Marinkovic
creator: Matej Babič
rights: Copyright (c) 2026 Nikola Komatina, Dragan Marinkovic, Matej Babič (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-01
publication date: 2026-01-01
starting page: 63
ending page: 80
doi: 10.31181/sor31202635

A Study on DEMATEL Approach Under Uncertainty Environments
type: item
description: A fuzzy set is a mathematical construct that assigns a membership grade to each element within a universe of discourse, representing the degree to which the element belongs to the set. This approach extends classical binary logic by allowing continuous values between 0 and 1, making it a natural framework for handling uncertainties and vague concepts often expressed in natural language. Fuzzy sets are particularly powerful in modelling real-world scenarios where ambiguity and imprecision are inherent, such as in human decision-making, linguistic expressions, and complex systems. This paper introduces a novel application of fuzzy logic by proposing a fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) method. DEMATEL is a well-established technique used to analyse cause-and-effect relationships within complex systems. Still, its traditional form relies on crisp values, which may not adequately capture the inherent uncertainties in real-world data. Our proposed method integrates triangular fuzzy numbers into the DEMATEL framework, enabling the representation and analysis of data with imprecision and vagueness. Specifically, we apply the fuzzy DEMATEL approach to study the cause-and-effect relationships among factors affecting transgender individuals, a population often marginalized and underrepresented in research. By leveraging triangular fuzzy numbers, our method provides a more nuanced and realistic representation of the uncertainties and complexities in the data. This approach not only enhances the accuracy of the analysis but also offers a meaningful way to interpret vague or subjective information, ultimately contributing to more informed decision-making and policy development for transgender communities.
subject: Articles
  topic: section
subject: Fuzzy theory
  topic: keywords
subject: Triangular fuzzy number
  topic: keywords
subject: Decision Making Trial and Evaluation Laboratory
  topic: keywords
subject: DEMATEL
  topic: keywords
subject: Decision making
  topic: keywords
subject: MCDM
  topic: keywords
creator: Saraswathi Appasamy
rights: Copyright (c) 2026 Saraswathi Appasamy (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-01
publication date: 2026-01-01
starting page: 29
ending page: 39
doi: 10.31181/sor31202628

Sustainable Urban Transportation: Key Criteria for a Greener Future
type: item
description: A sustainable transportation network has become increasingly critical for society as urban growth, environmental challenges, and transport system inefficiencies intensify. The seamless application of multi-criteria decision analysis (MCDA) as an analytical framework enables the identification, weighting, and ranking of key sustainability criteria across economic indicators, environmental factors, and social sustainability measures. The Fuzzy Logarithm Methodology of Additive Weights (F-LMAW) serves as an analytical tool to evaluate, weigh, and rank these criteria under uncertain conditions. In this study, F-LMAW—incorporating Triangular Fuzzy Numbers (TFNs)—is applied to assess sustainable transport criteria across different sustainability dimensions. The analysis integrates expert surveys, current literature, and findings from completed transportation projects to introduce five new sustainability criteria. The results reveal that safety, health, and greenhouse gas emissions are the most critical sustainability factors. Furthermore, transportation system design should prioritize human well-being and environmental protection. While economic factors, particularly infrastructure costs, remain essential, they must be evaluated alongside long-term operational sustainability requirements. This research provides a structured approach to help authorities systematize transportation funding decisions, optimize resource allocation, and integrate sustainable practices into urban transport systems.
subject: Articles
  topic: section
subject: Sustainable
  topic: keywords
subject: Transportation
  topic: keywords
subject: Multi-Criteria Decision-Analysis
  topic: keywords
subject: F-LMAW
  topic: keywords
subject: Fuzzy Set
  topic: keywords
creator: Kiana Nayeb-Pashaei
creator: Sahand Vahabzadeh
creator: Amin Hosseinian-Far
creator: Saeid Jafarzadeh Ghoushchi
rights: Copyright (c) 2026 Kiana Nayeb-Pashaei, Sahand Vahabzadeh, Amin Hosseinian-Far, Saeid Jafarzadeh Ghoushchi (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-01
publication date: 2026-01-01
starting page: 103
ending page: 127
doi: 10.31181/sor31202634

Fuzzy SIWEC and Fuzzy RAWEC Methods for Sustainable Waste Disposal Technology Selection
type: item
description: Rapid industrialization, population growth, and poor waste management have led to significant environmental and economic challenges. These issues underscore the need for effective disposal technologies to mitigate public health risks, reduce greenhouse gas emissions, and promote resource recovery. This study aims to determine the most suitable sustainable solid waste disposal technology for the planned Çivril Solid Waste Disposal Facility in Denizli Province. To evaluate eight disposal alternatives: landfilling (A₁), composting (A₂), biomethanization (A₃), incineration (A₄), gasification (A₅), plasma treatment (A₆), pyrolysis (A₇), and refuse-derived fuel (RDF) (A₈), we employed fuzzy-based Multi-Criteria Decision-Making (MCDM) methods: the Simple Weight Calculation (SIWEC) and Ranking Alternatives with Weights of Criterion (RAWEC). Twelve criteria, including environmental impact, legal compliance, and operational costs, were weighted using Fuzzy SIWEC, while the alternatives were ranked using Fuzzy RAWEC. The results identified composting (A₂) as the most suitable technology, whereas RDF (A₈) performed the worst. Validation through comparison with other MCDM methods (F-TOPSIS, F-SAW, F-MABAC, and CORASO) demonstrated high consistency. Sensitivity analysis confirmed that composting (A₂) and gasification (A₅) maintained stable rankings across different scenarios, while the rankings of other methods varied depending on decision-maker preferences. The integrated use of fuzzy-based SIWEC and RAWEC provides a reliable and systematic framework for sustainable waste management decision-making.
subject: Articles
  topic: section
subject: Fuzzy MCDM
  topic: keywords
subject: Fuzzy SIWEC
  topic: keywords
subject: Fuzzy RAWEC
  topic: keywords
subject: Sustainable waste management
  topic: keywords
creator: Ali Katrancı
creator: Nilsen Kundakcı
creator: Kevser Arman
rights: Copyright (c) 2026 Ali Katranci, Nilsen Kundakci, Kevser Arman (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-01
publication date: 2026-01-01
starting page: 87
ending page: 102
doi: 10.31181/sor31202633

Shadowed Offset: Integrating Offset and Shadowed Set Frameworks for Enhanced Uncertainty Modeling
type: item
description: Uncertainty‑handling frameworks—including Fuzzy Sets, Intuitionistic Fuzzy Sets, Hyperfuzzy Sets, Neutrosophic Sets, HyperNeutrosophic Sets, Soft Sets, Rough Sets, and Plithogenic Sets—have become fundamental tools for modeling imprecision and vagueness across diverse application domains. Classical fuzzy sets extend traditional set theory by assigning each element a membership degree within the unit interval [0,1], thereby capturing graded inclusion. To represent under‑ and over‑membership, many of these theories have been enriched with offset concepts that allow membership values to fall outside this canonical range. Shadowed sets complement these developments by employing two thresholds to partition the membership spectrum into three regions—excluded, included, and indeterminate—providing a compact mechanism for residual uncertainty. Despite the complementary strengths of offset and shadowed approaches, a unified formalism integrating both has not yet been explored. In this paper, we introduce the novel concept of the Shadowed Offset, which extends the shadowed‑set paradigm by permitting off‑interval membership while preserving tripartite thresholding. We present a rigorous mathematical definition of Shadowed Offsets, derive their fundamental properties, and illustrate their behavior through representative examples. The proposed construct offers a more flexible and expressive framework for complex uncertainty, and we conclude by outlining promising directions for future research.
subject: Articles
  topic: section
subject: Fuzzy Offset
  topic: keywords
subject: Fuzzy Set
  topic: keywords
subject: Shadowed Set
  topic: keywords
subject: Shadowed Offset
  topic: keywords
creator: Takaaki Fujita
rights: Copyright (c) 2025 Takaaki Fujita (Author) https://creativecommons.org/licenses/by/4.0
date: 2025-08-10
publication date: 2025-08-10
starting page: 1
ending page: 17
doi: 10.31181/sor4152

Decision-Making Framework for Urban Transportation Using Linear Diophantine Fuzzy Z-numbers with Dombi Aggregation, TOPSIS and VIKOR Methods
type: item
description: This study proposes an innovative approach to decision-making under uncertainty, using Pakistan’s urban transportation issues—particularly in cities like Karachi, Lahore, and Islamabad—as a case study. These cities face severe traffic congestion, demanding more effective strategies for infrastructure planning. We introduce a Linear Diophantine Fuzzy Z-Numbers (LDFZN) framework that captures membership and non-membership grades alongside the degree of reliability, addressing key limitations of traditional fuzzy systems by simultaneously considering uncertainty and confidence. Within this framework, we develop three decision-making methods: an LDFZN Dombi Weighted Averaging operator that aggregates expert opinions while accounting for their reliability; an adapted VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method for multi-criteria compromise solutions under LDFZN settings; and a modified Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) tailored for LDFZN-based scenarios. These tools are applied to real-world transportation challenges in Pakistan, demonstrating their effectiveness in managing uncertainty and expert-based confidence levels. The results outperform conventional models in decision robustness and clarity under uncertain conditions. This work contributes significantly to the theoretical and practical advancement of fuzzy mathematics, extending uncertainty modeling and providing practical solutions not only for transportation but also for various fields requiring informed decision-making with imprecise and unreliable data.
subject: Articles
  topic: section
subject: Fuzzy numbers
  topic: keywords
subject: Z-numbers
  topic: keywords
subject: Linear Diaphantine fuzzy Z-numbers
  topic: keywords
subject: Dombi operations
  topic: keywords
subject: Aggregation operator
  topic: keywords
subject: Multicriteria decision making algorithm
  topic: keywords
subject: TOPSIS
  topic: keywords
subject: VIKOR
  topic: keywords
creator: Rukhshanda Anjum
creator: Muhammad Umar Mirza
creator: Nasreen Kausar
creator: Rabia Ali
rights: Copyright (c) 2025 Rukhshanda Anjum, Muhammad Umar Mirza, Nasreen kausar, Rabia Ali (Author) https://creativecommons.org/licenses/by/4.0
date: 2025-07-18
publication date: 2025-07-18
starting page: 1
ending page: 34
doi: 10.31181/sor4155

Remote Sensing-Based Evaluation of Lake Area Dynamics: A Quantitative Assessment for Environmental Management in Turkey
type: item
description: This research employs remote sensing techniques and advanced image processing algorithms to analyze lake level changes. The study focuses on two major lakes in Turkey, Burdur and Salda, using satellite imagery from 2000 to 2024. The primary objective is to investigate spatial and temporal surface area changes over a one-year period. A key step in the process involves identifying water pixels in infrared band images through binarization and image processing, enabling accurate measurements of lake sizes and shapes. The results were evaluated using three criteria: R², RMSE, and MAPE. Findings showed that Burdur Lake experienced a 1.47% decrease, while Salda Lake had a smaller decline of 0.307% in 2024, attributed to drought and water resource availability.
subject: Articles
  topic: section
subject: Lake
  topic: keywords
subject: Satellite Image
  topic: keywords
subject: Remote Sensing Data
  topic: keywords
subject: Model
  topic: keywords
creator: Shahryar Ghorbani
creator: Dragan Pamucar
rights: Copyright (c) 2026 Shahryar Ghorbani, Dragan Pamucar (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-01
publication date: 2026-01-01
starting page: 352
ending page: 358
doi: 10.31181/sor31202653

Solution of Fuzzy System of Linear Equation Under Different Fuzzy Difference Ideology
type: item
description: Fuzzy arithmetic includes distinctive notions regarding differences between fuzzy numbers, which impact the defining characteristics of fuzzy-valued calculus. In this article, we consider the Hukuhara and generalized Hukuhara differences of fuzzy numbers for solving systems of linear equations under fuzzy-rule uncertainty within an analytical framework. Moreover, the discussion of solutions in parametric form includes existence and uniqueness criteria. Numerical examples and graphical representations are provided to illustrate the proposed theory.
subject: Articles
  topic: section
creator: Payel Sing
creator: Mostafijur Rahaman
creator: Sankar Prasad Mondal Sankar
rights: Copyright (c) 2024 Payel Sing, Mostafijur Rahaman, Sankar Prasad Mondal Sankar (Author) https://creativecommons.org/licenses/by/4.0
date: 2024-08-06
publication date: 2024-08-06
starting page: 64
ending page: 74
doi: 10.31181/sor1120244

A Decision-Making Framework for Sustainable Highway Restaurant Site Selection: AHP-TOPSIS Approach based on the Fuzzy Numbers
type: item
description: This research work indicates the site selection problem for a restaurant beside the highway. It is really challenging as well as demanding work. It mainly depends on the cost of the selected location, transportation, parking facilities, hygienic atmosphere, distance from the city, etc. In this paper, the proposed site selection problem is constructed and solved by using a fuzzy Multi-Criteria Decision Making (MCDM) process. The two methods of MCDM that we use here, namely the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), are used to calculate criteria weights and rank the proposed restaurant locations, respectively. Multiple decision makers’ (DMs) opinions are considered for data collection, and Trapezoidal Fuzzy Numbers (TrFNs) are taken as uncertainty tools to deal with uncertainty. Finally, we perform sensitivity and comparative analyses to verify the system's vagueness and flexibility.
subject: Articles
  topic: section
subject: Restaurant site selection
  topic: keywords
subject: Trapezoidal Fuzzy Number (TrFN)
  topic: keywords
subject: AHP
  topic: keywords
subject: TOPSIS
  topic: keywords
creator: Aditi Biswas
creator: Kamal Hossain Gazi
creator: Prasad Mondal Sankar
creator: Arijit Ghosh
rights: Copyright (c) 2025 Aditi Biswas, Kamal Hossain Gazi, Prasad Mondal Sankar, Arijit Ghosh (Author) https://creativecommons.org/licenses/by/4.0
date: 2025-01-01
publication date: 2025-01-01
starting page: 1
ending page: 26
doi: 10.31181/sor2120256

On the Anticancer Drug Structures and Their Locating Numbers
type: item
description: Cancer is the rapid proliferation of unwanted cells in the body. Carcinogens are chemicals that can cause cancer. A carcinogen is a type of chemical compound found in cigarette smoke. It has the ability to spread to many parts of the body. Some of the signs and symptoms of this disease include lumps, irregular bleeding, chronic cough, weight gain or loss, and so on. Tobacco chewing is a major factor in this deadly disease. Obesity, a poor diet, physical inactivity, and increased alcohol consumption are also contributing factors. Anticancer drugs are used to treat this condition. In this work, we studied some anticancer medicines in terms of locating sets, where a locating set is a set used to resolve the entire atom set of a graph in a unique way, allowing each atom to be accessed independently. By locating numbers, a particular resolving set is chosen, and this resolving set, or locating set, transforms the entire structure into a unique form. This helps in studying the chemical structure in greater depth and detail. Thus, the locating number helps to understand the chemical structure more comprehensively. The locating number is part of resolvability parameters and also plays a role in developing a unique way to access each node or vertex of a network. When each vertex is easily accessible with a unique code, working with a network becomes easier. Therefore, this method makes the structures of anticancer drugs more understandable and allows researchers to further extend their work on these structures in medical diagnostics.
subject: Articles
  topic: section
subject: Anticancer Drug Structures
  topic: keywords
subject: Vertex Metric Dimension
  topic: keywords
subject: Locating Number
  topic: keywords
subject: Locating Set
  topic: keywords
creator: Muhammad Azeem
creator: Muhammad Kamran Jamil
rights: Copyright (c) 2024 Muhammad Azeem, Muhammad Kamran Jamil (Author) https://creativecommons.org/licenses/by/4.0
date: 2024-08-04
publication date: 2024-08-04
starting page: 44
ending page: 63
doi: 10.31181/sor1120245

Optimizing Vendor-Managed Inventory in Multi-Tier Distribution Systems
type: item
description: This paper addresses the concept of the vendor-managed inventory (VMI) problem, focusing on the replenishment policy and the vehicle routing problem (VRP) model. These components are integrated to tackle a three-echelon distribution issue comprising a single plant, multiple depots, and multiple retailers, with the primary objective of minimizing transportation and inventory costs within this complex distribution network. A three-phase methodology is proposed to optimize the entire supply chain, from the plant to the final retailer, and its performance is evaluated through computational experiments. This research is motivated by a real-life supply network, highlighting its practical relevance and applicability. To extend the capabilities of existing methods for solving the combined inventory and routing problem, an insertion heuristic is incorporated to enhance vehicle utilization, thereby reducing total costs. Computational results demonstrate the effectiveness of the improved algorithm, indicating that it is sufficiently robust for practical application. Significant cost savings can be achieved with the proposed approach, making it a valuable contribution to the field of supply chain optimization.
subject: Articles
  topic: section
subject: Vendor Managed Inventory
  topic: keywords
subject: Routing Problem
  topic: keywords
subject: Nearest Neighbor Algorithm
  topic: keywords
subject: Stem Distance
  topic: keywords
subject: Insertion Heuristics
  topic: keywords
creator: Ibrahim Badi
creator: Mouhamed Bayane Bouraima
creator: Željko Stević
creator: Elizabeth Abosede Oloketuyi
creator: Opeyemi Oluyemisi Makinde
rights: Copyright (c) 2024 Ibrahim Badi, Mouhamed Bayane Bouraima, Željko Stević, Elizabeth Abosede Oloketuyi, Opeyemi Oluyemisi Makinde (Author) https://creativecommons.org/licenses/by/4.0
date: 2024-07-27
publication date: 2024-07-27
starting page: 33
ending page: 43
doi: 10.31181/sor1120243

A Framework for Extensive Content-Based Image Retrieval System Incorporating Relevance Feedback and Query Suggestion
type: item
description: Over the last decade, there has been a huge increase in the number of images, in which visual information has become increasingly important. If images are to be utilized, they must be organized into databases, from which they can be searched based on different criteria. Content-Based Image Retrieval (CBIR) frameworks have become a mainstream subject of research due to their ability to retrieve images based on actual visual content rather than manually assigned textual descriptions. In the CBIR framework, the analysis and interpretation of image information in large and diverse image databases are evidently complex because there is no prior information about the size or scale of individual structures within the images to be analyzed. In CBIR, retrieval is based on visual image features, which can be extracted automatically from images with the help of human intervention through a technique known as relevance feedback. Nonetheless, efficient methods for differentiating the visual content of images are complex to develop. Therefore, rather than providing a perfect solution, CBIR systems must be able to exploit partial solutions to the problem of image understanding. In this paper, an implementation of a CBIR framework is introduced that not only attempts to efficiently capture user intent based on feedback but also provides query suggestions that help users formulate better queries to retrieve desired results efficiently. The proposed technique is straightforward to implement and scales efficiently to large datasets. Extensive experiments on diverse real-world datasets using image similarity measures have revealed the superiority of the proposed method over existing algorithms.
subject: Articles
  topic: section
subject: Relevance Feedback
  topic: keywords
subject: Content Based Image Retrieval
  topic: keywords
subject: Random Walker
  topic: keywords
creator: Rabia Younas
creator: Hafiz Burhan Ul Haq
creator: Muhammad Daniyal Baig
rights: Copyright (c) 2024 Rabia Younas, Hafiz Burhan Ul Haq, Muhammad Daniyal Baig (Author) https://creativecommons.org/licenses/by/4.0
date: 2024-07-27
publication date: 2024-07-27
starting page: 13
ending page: 32
doi: 10.31181/sor1120242

Best Practice Performance of COVID-19 in America continent with Artificial Intelligence
type: item
description: Metaheuristics were employed with ANFIS and K-means to determine whether COVID-19 performed the best on the American continent. A few individuals lost their lives to COVID-19, and quite a few nations assisted with this matter. It is essential to know the nations that performed the best in COVID-19 management. Researchers can carry out evaluations of nations using metaheuristic approaches and ANFIS. Based on the performance of these nations, clusters will be determined and established. The research excluded only two of the thirteen criteria that were investigated. Seven distinct groups have been established for each of the thirty-five nations. In the United States, the performance regarding COVID-19 is the poorest, according to the research. These three nations also had the most extraordinary response to the COVID-19 outbreak. Based on the methodology and the context of the literature evaluation, this work’s contribution may be divided into two distinct areas. The existence of research gaps makes it clear that a regional emphasis is needed rather than a focus on a nation or a portion of a country, which illustrates the requirement for a focus on the whole continent.
subject: Articles
  topic: section
subject: COVID-19
  topic: keywords
subject: Performance Measurement
  topic: keywords
subject: ANFIS Method
  topic: keywords
subject: K-means Method
  topic: keywords
subject: Meta-Heuristics Method
  topic: keywords
creator: Amir Karbassi Yazdi
creator: Hossein Komasi
rights: Copyright (c) 2024 Amir Karbassi Yazdi, Hossein Komasi (Author) https://creativecommons.org/licenses/by/4.0
date: 2024-07-27
publication date: 2024-07-27
starting page: 1
ending page: 12
doi: 10.31181/sor1120241

Parametric Analysis and ANN Prediction of Biogas Yield from Anaerobic Biochemical Reactions of Non-Uniform Organic Substrates under Mesophilic Regime
type: item
description: In an attempt to acquire affordable energy alternatives, without deviating from sustainable waste management goals, researchers in recent times have explored a number of options to expand the frontiers of research on biogas recovery. Thus, this study explores the optimization of biogas production through mesophilic anaerobic digestion (AD) of heterogeneous, non-uniform substrates. By comparing mono-digestion with co-digestion techniques, a thorough parametric analysis experimentally assessed the effects of temperature, moisture content, and pH on biogas yield. Under these intricate and fluctuating substrate conditions, an ANN model was developed to predict the biogas-yielding output from the same experimental conditions. The results of the experiment revealed different ideal temperature ranges: co-digestion produced larger yields throughout a wider range of 28.2–30.6°C, whereas mono-digestion peaked between 26°C and 28°C. Mono-digestion produced a maximum of 0.22 g/day at 26.4–29.3°C at 15% moisture content, whereas co-digestion increased production to 0.26 g/day at 28.2–31.6°C. A maximum experimental output of 0.26 g/day for co-digestion was found by pH adjustment. The ANN results showed remarkable accuracy, nearly matching pH-driven co-digestion yields (prediction: 0.27 g/day vs. experimental: 0.26 g/day) and reproducing experimental moisture-driven yields (0.22 g/day for mono-digestion). This demonstrates how well the model captures the non-linear interactions present in the digestion of various feedstock. It was further observed that biogas yield and temperature increase in pari passu. Biogas yield was also observed to be significant at pH values within the neutral range, indicating rich substrate content and a favourable bio-digester environment for microbial activities. Comparatively, an increase in moisture content led to a more significant biogas yield than other experimental conditions. The study unequivocally demonstrates that co-digestion is one of the be…
subject: Articles
  topic: section
subject: Biogas Yield
  topic: keywords
subject: Bio-digester
  topic: keywords
subject: Anaerobic digestion
  topic: keywords
subject: Organic substrates
  topic: keywords
subject: ANN prediction
  topic: keywords
subject: Mesophilic regime
  topic: keywords
subject: Renewable energy
  topic: keywords
subject: Waste management
  topic: keywords
creator: Aniekan Essienubong Ikpe
creator: Imoh Ime Ekanem
creator: Michael Okon Bassey
rights: Copyright (c) 2025 Aniekan Essienubong Ikpe, Imoh Ime Ekanem, Michael Okon Bassey (Author) https://creativecommons.org/licenses/by/4.0
date: 2025-11-22
publication date: 2025-11-22
starting page: 1
ending page: 18
doi: 10.31181/sor41202759

An Expert Opinion-Based Soft Computing Framework for Comparing Nanotechnologies used in Agriculture
type: item
description: Nanotechnology (NT) has revolutionized agriculture through precision farming, environmental protection, enhanced nutrient delivery and crop production, and effective pesticide control. The purpose of the present research is twofold. First, it aims to develop a novel soft computing model for multi-criteria decision analysis (MCDA) by proposing an Interval-valued p, q–Quasirung Orthopair Fuzzy Number (p, q–IVQROFN)-based hybrid MCDA framework. The CIMAS (Criteria Importance Assessment) method is employed to determine the weights of the criteria, while the WISP method ranks the alternatives. This paper introduces a modification to the WISP method by aggregating four distinct utility degrees using the Heron Mean. The second objective is to apply the proposed framework to compare leading NTs used in agriculture. An expert group decision-making approach is developed to evaluate eight NTs, guided by the theoretical frameworks of TOE (Technology–Organization–Environment) and TRI (Technology Readiness Index). Alternatives are ranked using experts’ ratings within the proposed framework, followed by a risk assessment using the Fine–Kinney framework (FKF) to identify potential vulnerabilities. The NTs are compared based on both performance and risk profiles. The results indicate that nano-sensors (NT5), nano-fungicides (NT3), nano-fertilizers (NT2), nano-clays (NT6), and nano-herbicides (NT4) rank as the top nanotechnologies for agricultural applications. The reliability of the proposed model is confirmed through comparisons with other MCDA methods and sensitivity analysis. Overall, this paper presents a robust and practical methodology for sustainable agricultural planning.
subject: Articles
  topic: section
subject: Sustainable Agriculture
  topic: keywords
subject: Interval-valued p, q – Quasirung Orthopair Fuzzy Number
  topic: keywords
subject: CIMAS
  topic: keywords
subject: WISP
  topic: keywords
creator: Sanjib Biswas
creator: Sandeep Bhattacharjee
creator: Biplab Biswas
creator: Kaushik Mitra
creator: Nibir Khawas
rights: Copyright (c) 2025 Sanjib Biswas, Sandeep Bhattacharjee, Biplab Biswas, Kaushik Mitra, Nibir Khawas (Author) https://creativecommons.org/licenses/by/4.0
date: 2025-08-12
publication date: 2025-08-12
starting page: 1
ending page: 39
doi: 10.31181/sor4156

Review of Probabilistic HyperGraph and Probabilistic SuperHyperGraph
type: item
description: Uncertainty pervades many real-world networks, yet existing models such as probabilistic graphs and hypergraphs capture only pairwise or fixed-order interactions. We introduce the novel concept of Probabilistic n-SuperHyperGraphs, which unify nested higher-order relationships with edge-level uncertainty by assigning probabilities to “superedges” at multiple powerset levels. We present a rigorous formal framework, derive fundamental properties—including degree–sum identities and closure under substructure—and show that our model subsumes classical probabilistic graphs and hypergraphs as special cases. These results pave the way for more expressive and scalable methods in modeling and analyzing complex, uncertainty-laden systems across diverse application domains.
subject: Articles
  topic: section
subject: SuperHyperGraph
  topic: keywords
subject: HyperGraph
  topic: keywords
subject: Probabilistic HyperGraph
  topic: keywords
subject: Probabilistic SuperHyperGraph
  topic: keywords
subject: Probabilistic Graph
  topic: keywords
subject: Probability
  topic: keywords
creator: Takaaki Fujita
rights: Copyright (c) 2026 Takaaki Fujita (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-01
publication date: 2026-01-01
starting page: 319
ending page: 338
doi: 10.31181/sor31202651

Multi-Criteria Evaluation of Wind Turbines using Entropy-based-TOPSIS and CoCoSo Methods: Insights from a Turkish Case Study
type: item
description: This study evaluated different alternatives using entropy-based TOPSIS and CoCoSo techniques, which are multi-criteria decision-making (MCDM) methods, to optimise the decision-making process in wind turbine selection. The study considered six criteria: price, rated power, rotor diameter, turbine size, noise emission value, and annual energy production. As a result of the analyses, Wind turbine-3 and Wind turbine-4 were the most suitable options. The findings revealed that criteria such as energy efficiency, sizeable nominal power, and minimisation of sound emission play a critical role in wind turbine selection. The findings of this study provide a more objective and analytical approach for decision-makers in wind energy projects. The Entropy-based TOPSIS and CoCoSo methodologies used in this study provide consistent and reliable results in evaluating alternatives. In particular, the fact that the CoCoSo method obtains similar rankings with TOPSIS shows that the methods can complement each other in multi-criteria decision-making problems.
subject: Articles
  topic: section
subject: CoCoSo
  topic: keywords
subject: TOPSIS
  topic: keywords
subject: Multi-criteria decision making
  topic: keywords
subject: Wind turbines
  topic: keywords
subject: Renewable energy
  topic: keywords
creator: Melisa Şahin
creator: Derya Deliktaş
rights: Copyright (c) 2026 Melisa Şahin, Derya Deliktaş (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-01
publication date: 2026-01-01
starting page: 339
ending page: 351
doi: 10.31181/sor31202650