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1
Fattoruso, Gerarda. "Multi-Criteria Decision Making in Production Fields: A Structured Content Analysis and Implications for Practice." Journal of Risk and Financial Management 15, no. 10 (2022): 431. http://dx.doi.org/10.3390/jrfm15100431.
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As the complexity of decision-making problems and the competitiveness in which companies find themselves carrying out their activities increase, the need to use tools that can help Decision-Makers (DM) make more informed and more effective choices increases. Multi-Criteria Decision Making (MCDM) represents a valid decision support tool capable of simplifying the process of choosing, ranking or sorting the alternatives that characterize the problem. This work aims to investigate with a structured content analysis if MCDMs are used in an extremely complex and competitive sector such as the automotive sector. The work also aims to describe and explore in the existing literature the role that entrepreneurs (our decision-makers) play in the construction of MCDM methods. The results show that MCDMs are widely used in different application areas in the domain of interest and that the decision maker is involved in several phases of construction of the MCDM methods.
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Saeed, Mohamed Osman, Hamidi Abdul Aziz, and Khairun Azizi Mohd Azizli. "The Art of Integrated GIS/AHP for Siting Landfill: A Review." Applied Mechanics and Materials 567 (June 2014): 144–49. http://dx.doi.org/10.4028/www.scientific.net/amm.567.144.
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This article reviewed selected works on how decision makers (DMs) utilize integrated geographic information system (GIS)/analytical hierarchy process (AHP) tools to analyze land suitability for sanitary landfill sites as part of regional planning. We analyzed the hierarchy process of certain pervious works to facilitate better understanding. The innovative work of Siddiqi et al. in 1996 highlighted the advantages of integrating AHP in GIS software and reviewed some limitations. The present paper explained the background study on multi-criteria decision analysis/aid (MCDA) so-called multi-criteria decision makers (MCDM) in conjunction with the advantages of GIS as a new remedy for utilizing the AHP weights of the decision makers. For this study we often use the term MCDA and MCDM.
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Guebsi, Wafa, and Alaeddine Zouari. "Investigation on Multi-Criteria Decision Making Methods Application in Sustainable Product Design." SPEKTA (Jurnal Pengabdian Kepada Masyarakat : Teknologi dan Aplikasi) 3, no. 1 (2022): 91–104. http://dx.doi.org/10.12928/spekta.v3i1.5962.
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Background: Integrating sustainability development' aspects in the design process is becoming, a growth area in companies. Consequently, sustainable product design has to consider the different aspects of sustainability throughout its life cycle phases in addition of other requirements. This integration is becoming more complicated due the difficulty of managing the constraints and alternatives related to the product and stakeholders needs. This study aims to highlights the most used Multi-Criteria Decision Making (MCDM) tools and methods used in sustainable product design process. Contribution: Product design process involves interesting decisional tasks such as the choice of materials, standard parts, technical solutions. Hence, the contribution of this work is to help designer to adopt relevant MCDM tools and methods that can be integrated to other tools to facilitate and to justify their decisional tasks. Method: Several methods have been affected to solve the problems related to this complexity such as MCDM. A literature review was conducted based on Siencedirect and GoogleScholar articles databases. After filtering more than 200 articles only 62 articles were considered to analyze the correlation between sustainable product design and MCDM. Results: Classified MCDM use according to the type of choices to achieve SPD goals. This paper allowed us to find matches between MCDM methods and SPD problem. The majority of case studies result show that a large portion of sustainable design methods, techniques, and tools are applied to the sustainable product’ along its different life cycle phases Conclusion: It is noticed that the use of MCDM methods are an important outcome in the sustainable product design process and deeply helps designers to make suitable choices. Also, several matches relating MCDM, other methods and sustainable product design sphere are discussed
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Madić, Miloš, Miroslav Radovanović, Dušan Petković, and Bogdan Nedić. "Selection Of Cutting Inserts For Aluminum Alloys Machining By Using MCDM Method." ACTA Universitatis Cibiniensis 66, no. 1 (2015): 98–101. http://dx.doi.org/10.1515/aucts-2015-0035.
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Abstract Machining of aluminum and its alloys requires the use of cutting tools with special geometry and material. Since there exists a number of cutting tools for aluminum machining, each with unique characteristics, selection of the most appropriate cutting tool for a given application is very complex task which can be viewed as a multi-criteria decision making (MCDM) problem. This paper is focused on multi-criteria analysis of VCGT cutting inserts for aluminum alloys turning by applying recently developed MCDM method, i.e. weighted aggregated sum product assessment (WASPAS) method. The MCDM model was defined using the available catalogue data from cutting tool manufacturers.
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Taherdoost, Hamed, and Mitra Madanchian. "Multi-Criteria Decision Making (MCDM) Methods and Concepts." Encyclopedia 3, no. 1 (2023): 77–87. http://dx.doi.org/10.3390/encyclopedia3010006.
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Multi-criteria decision-making (MCDM) is one of the main decision-making problems which aims to determine the best alternative by considering more than one criterion in the selection process. MCDM has manifold tools and methods that can be applied in different fields from finance to engineering design. This entry aims to provide a survey on the MCDM concept, its applications, main categories, and different methods. The final section provides manifold information and statistics on the published works in the MCDM fields. Some of the main methods are also listed in this section.
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Dymova, Ludmila, Krzysztof Kaczmarek, Pavel Sevastjanov, and Joanna Kulawik. "A Fuzzy Multiple Criteria Decision Making Approach with a Complete User Friendly Computer Implementation." Entropy 23, no. 2 (2021): 203. http://dx.doi.org/10.3390/e23020203.
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The paper presents the generalization of the almost forty years of experience in the field of setting and solving the multiple criteria decision-making (MCDM) problems in various branches of a human activity under different types of uncertainties that inevitably accompany such problems. Based only on the pragmatic intentions, the authors avoid the detailed descriptions of the known methods for the decision-making, while instead focusing on the most frequently used mathematical tools and methodologies in the decision-making practice. Therefore, the paper may be classified as a special kind of illustrative review of the mathematical tools that are focused on applications and are the most used in the solutions of MCDM problems. As an illustrative example, a complete user-friendly computer implementation of such tools and methodology is presented with application to the simple “buying a cat” problem, which, however, possesses all the attributes of the hierarchical fuzzy MCDM task.
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YÜKSEL, Fatma Şeyma, Ayşe Nilgün KAYADELEN, and Figen ANTMEN. "A systematic literature review on multi-criteria decision making in higher education." International Journal of Assessment Tools in Education 10, no. 1 (2023): 12–28. http://dx.doi.org/10.21449/ijate.1104005.
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The three components that form the basis of the educational process are the teacher, the learner, and the environment. These three components are affected by the developing and changing technology as a result of globalization considerably. Teaching and learning techniques should be updated and connected with these developments; new tools are therefore needed to make the necessary updates. Determination and application of the new tools include many decisions. Decision-makers can make more effective decisions using Multi-Criteria Decision-Making Techniques (MCDM), a complex decision-making tool that includes both quantitative and qualitative factors at present time. This study aimed to determine which MCDM methods are used in studies conducted in higher education, which is one of the most important development level indicators of countries, and to present a systematic literature review of MCDM method applications. The study was conducted in three stages: first, known electronics were searched until the end of 2021 using keywords; then, all studies were listed in a systematic taxonomy, and in the last stage, Thematic Network Analysis was used to evaluate the development of MCDM studies in the higher education area. It is determined that the Analytical Hierarchy Process (AHP) method is the most widely used method in higher education in MCDM applications. It was observed that the most common use of MCDM applications in higher education is e-learning as well. This study aims to be a guide for all researchers and practitioners who will study in both higher education and the MCDM areas.
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Malefaki, Sonia, Dionysios Markatos, Angelos Filippatos, and Spiros Pantelakis. "A Comparative Analysis of Multi-Criteria Decision-Making Methods and Normalization Techniques in Holistic Sustainability Assessment for Engineering Applications." Aerospace 12, no. 2 (2025): 100. https://doi.org/10.3390/aerospace12020100.
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The sustainability evaluation of engineering processes and structures is a multifaceted challenge requiring the integration of diverse and often conflicting criteria. To address this challenge, Multi-Criteria Decision-Making (MCDM) methods have emerged as effective tools. However, the selection of the most suitable MCDM approach for problems involving multiple criteria is critical to ensuring robust, reliable, and actionable outcomes. Equally significant is the choice of a proper normalization technique, which plays a pivotal role in determining the robustness and reliability of the results. This study investigates the impact of common MCDM tools on the decision-making process concerning diverse aspects of sustainability. It also examines how different normalization methods influence the final outcomes. Sustainability in this context is understood as a trade-off among five key dimensions: performance, environmental impact, economic impact, social impact, and circularity. The outcome of the MCDM process is represented by an aggregated metric, referred to as the Sustainability Index (SI). This index offers a comprehensive and robust framework for evaluating sustainability and facilitating decision-making when conflicting criteria are present. To assess the effects of implementing different MCDM and normalization choices on the sustainability assessment, a dataset from the aviation sector is employed. Specifically, a typical aircraft component is analyzed as a case study for holistic sustainability assessment, utilizing data that represent the various dimensions of sustainability mentioned above, for this component. Additionally, the study investigates the influence of initial data variations and weight variations within the MCDM process on the results. The results indicate that, overall, the different MCDM and normalization methods lead to similar outcomes when applied to the design alternatives. However, a deeper dive into the results reveals that the weighted sum method, when paired with min-max normalization, appears to be more appropriate, based on the use case involved for the present investigation, due to its robustness regarding small variations in the initial data and its sensitivity to large ones. This research underscores the critical importance of selecting appropriate MCDM tools and normalization methods to enhance transparency, robustness, reliability, and consistency of sustainability assessments within a holistic framework.
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Paul, Ananna, Nagesh Shukla, Sanjoy Kumar Paul, and Andrea Trianni. "Sustainable Supply Chain Management and Multi-Criteria Decision-Making Methods: A Systematic Review." Sustainability 13, no. 13 (2021): 7104. http://dx.doi.org/10.3390/su13137104.
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Multi-criteria decision-making (MCDM) methods are smart tools to deal with numerous criteria in decision-making. These methods have been widely applied in the area of sustainable supply chain management (SSCM) because of their computational capabilities. This paper conducts a systematic literature review on MCDM methods applied in different areas of SSCM. From the literature search, a total of 106 published journal articles have been selected and analyzed. Both individual and integrated MCDM methods applied in SSCM are reviewed and summarized. In addition, contributions, methodological focuses, and findings of the reviewed articles are discussed. It is observed that MCDM methods are widely used for analyzing barriers, challenges, drivers, enablers, criteria, performances, and practices of SSCM. In recent years, studies have focused on integrating more than one MCDM method to highlight methodological contributions in SSCM; however, in the literature, limited research papers integrate multiple MCDM methods in the area of SSCM. Most of the published articles integrate only two MCDM methods, and integration with other methods, such as optimization and simulation techniques, is missing in the literature. This review paper contributes to the literature by analyzing existing research, identifying research gaps, and proposing new future research opportunities in the area of sustainable supply chain management applying MCDM methods.
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Dhanalakshmi, G., S. Sandhiya, and Florentin Smarandache. "Selection of the best process for desalination under a Treesoft set environment using the multi-criteria decision-making method." International Journal of Neutrosophic Science 23, no. 3 (2024): 140–47. http://dx.doi.org/10.54216/ijns.230312.
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Multi-criteria decision-making (MCDM), which has been called a revolution in the field, is one of the most exact methods for making decisions. Multicriteria decision-making (MCDM) is the process of selecting options by considering multiple criteria to determine which is best. A multitude of applications in engineering, design, and finance are possible with the tools and methods derived from MCDM. Application-oriented problems with multiple criteria involve ambiguous and more inaccurate options, to deal with this ambiguity Smarandache introduced Treesoft sets, which are an extension of hypersoft sets. So, in this paper, we will consider a real-life application-oriented problem “Desalination process” under the treesoft sets environment and find the best method for desalination using one of the MCDM methods.
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Habib, Qasim, Hafiz Muhammad Khurram Ali, and Syed Muhammad Owais. "Sustainability Assessment of Quality 4.0 Tools in Telecom Industry." International Journal of Advanced Natural Sciences and Engineering Researches 7, no. 5 (2023): 100–104. http://dx.doi.org/10.59287/ijanser.909.
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The fourth industrial revolution, also commonly known as Industry 4.0, has brought about significant advancements in areas such as connection, mobility, analytics, scalability, and data, which have resulted in a complete transformation of the service and manufacturing industry. Quality 4.0 is an approach that integrates technology and data into quality management systems while also retaining traditional methods. This approach enhances value by facilitating modifications through culture, leadership, and collaboration. This paper aims to evaluate the sustainability and effectiveness of Quality 4.0 tools in the telecom industry by utilizing advanced Multi-Criteria Decision-Making (MCDM) techniques. The study seeks to analyze the impact of Quality 4.0 tools on both the quality management system and the overall sustainability of a telecom company through a combination of quantitative and qualitative data collection methods. The study has identified four crucial parameters of sustainability that significantly impact the sustainability evaluation of Quality 4.0 tools. It is focused on the telecom industry, specifically within the quality department, and identifies three potential tools for Quality 4.0 that are considered alternatives within the MCDM method. To effectively evaluate the effectiveness of these tools, the study utilizes the Analytic Hierarchy Process (AHP) techniques of MCDM. The results of this study provide a comprehensive overall ranking of the alternative tools, while a sensitivity analysis based on sustainability criteria demonstrates that the ranking of the alternatives can change based on specific sustainability factors. This groundbreaking research sheds invaluable light on the sustainability and effectiveness of Quality 4.0 hybrid tools in the telecom industry, providing valuable insights and practical recommendations for organizations considering their adoption.
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Osintsev, N. A. "Multi-Criteria Decision-Making Methods in Green Logistics." World of Transport and Transportation 19, no. 5 (2022): 105–14. http://dx.doi.org/10.30932/1992-3252-2021-19-5-13.
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Due to the increased demands of the world community in accordance with the goals of the concept of sustainable development, supply chain management requires complex decisionmaking models that consider many environmental, economic, and social constraints when implementing various environmentally friendly, green methods and technologies. An effective tool in such conditions is the use of MCDM, multi-criteria decision-making methods. The objective of the research, the results of which are provided in the article, is to analyse the application of MCDM in green logistics and management of green supply chains. The work used a set of methods including system and structural-functional analysis, methods of the theory of fuzzy sets, mathematical statistics, and expert assessments. A general scheme of MCDM implementation is offered and a combined MCDM model is developed for assessing decisions on the choice of green technologies, including a system of indicators for logistics flows, a model for managing logistics flows and a system of tools for green logistics. In the MCDM model, a fuzzy analytical hierarchical process (fuzzy AHP) is used to establish the weight of indicators of logistics flows, eleven MCDM methods are used to rank green logistics tools: SAW, TOPSIS, PROMETHEE, COPRAS, ARAS, WASPAS, MAIRCA, EDAS, MABAC, CODAS, MARCOS. Comparison of the use of various MCDM methods showed a high convergence of the ranking results (Spearman’s rank correlation coefficient is of 0.949). The most consistent are SAW, MARCOS and WASPAS methods, the least consistent are CODAS methods. The results of the design example showed that the most preferable solution is the «use of intermodal technologies and multimodal transportation» (ranked first within all eleven methods), the least preferable solution is the «use of environmentally friendly fuels and lubricants (fuels)» (ranked 12th within 10 methods of 11).
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Bozkurt Uzan, Şeyma. "Facilitating Decision-Making Processes in Packaging and Graphic Media: A Review of MCDM Methods from 2008 to 2024." Sakarya University Journal of Computer and Information Sciences 8, no. 2 (2025): 286–300. https://doi.org/10.35377/saucis...1596931.
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This study reviews how Multi-Criteria Decision Making (MCDM) methods, like AHP, TOPSIS, and VIKOR, transform packaging and graphic media decision-making. These tools simplify complex choices by evaluating multiple criteria, aiding in tasks like material selection and design optimization. The findings highlight that MCDM improves decision-making efficiency, accuracy, and sustainability. It also emphasizes the potential of integrating these methods with AI and machine learning to unlock further innovation. The study calls for standardizing data practices and fostering global collaborations to drive progress. This research provides a practical guide to harnessing MCDM for smarter, sustainable industry practices.
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Abu, R., M. A. A. Aziz, and Z. Z. Noor. "Integrated Life Cycle Assessment, Life Cycle Costing and Multi Criteria Decision Making for Food Waste Composting Management." Journal of Advanced Research in Business and Management Studies 21, no. 1 (2021): 1–9. http://dx.doi.org/10.37934/arbms.21.1.19.
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The integrated models specifically designed to help decision-making in food waste (FW) composting management through the analysis of previous research studies are reviewed. The integrated models are built predominantly within three decision-supporting tools, which include life-cycle assessment (LCA), life cycle costing (LCC), and multi-criteria decision-making (MCDM). Different integrated models were discussed and their strengths, limitations, and crucial problems as well as their potential integration were evaluated. Apparently, there has been no in-depth analysis of its approaches and potentialities of combining harmonically the LCA, LCC, and MCDM analysis tools in the FW composting management which taking into consideration multiple stakeholders. Thus, the combined LCA, LCC and MCDM with cluster analysis (CA) is suggested. The concepts underlying the sustainable FW composting management model can be divided into several aspects in terms of environmental friendliness, financial profitability, and social acceptance. This gives an insight and facilitates to waste management sectors to decide on a preferable FW composting management.
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Goswami, Shankha Shubhra, and Dhiren Kumar Behera. "Developing Fuzzy-AHP-Integrated Hybrid MCDM System of COPRAS-ARAS for Solving an Industrial Robot Selection Problem." International Journal of Decision Support System Technology 15, no. 1 (2023): 1–38. http://dx.doi.org/10.4018/ijdsst.324599.
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Robots are one of the most commonly used automated material handling equipment (MHE) in an industry, installed to perform a variety of hazardous and repetitive tasks, e.g., loading, unloading, pick-and-place operations, etc. The selection of an appropriate industrial robot is influenced by a number of subjective and objective factors that define its characteristics and working accuracy. As a result, robot selection can be regarded as a multi-criteria decision-making problem. In this article, a new hybrid MCDM model combining COPRAS and ARAS is developed to execute an industrial robot selection process based on three alternatives and five criteria. Fuzzy analytic hierarchy process is integrated to compute the parametric weights. It is discovered that Robot 3 and Robot 1 are coming out to be the best and worst alternative robots from this hybrid model. Finally, comparative analysis among eight other MCDM tools and sensitivity analysis are also performed to assess the stability and robustness of the developed hybrid model and other applied MCDM tools.
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Anysz, Hubert, Aleksander Nicał, Željko Stević, Michał Grzegorzewski, and Karol Sikora. "Pareto Optimal Decisions in Multi-Criteria Decision Making Explained with Construction Cost Cases." Symmetry 13, no. 1 (2020): 46. http://dx.doi.org/10.3390/sym13010046.
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In multi-criteria decision-making (MCDM) problems the decision-maker is often forced to accept a not ideal solution. If the ideal choice exists, it would be certainly chosen. The acceptance of a non- ideal solution leads to some inadequate properties in the chosen solution. MCDM methods help the decision-maker to structure his needs considering different units, in which the properties of the solutions are expressed. Secondly, with MCDM tools the assessment of the available solutions can be calculated with consideration of the decision-maker’s needs. The incorporation of the cost criterion into the decision maker’s preferences calculation, and the solution assessment calculation, deprives the decision-maker of the ability to calculate the financial result of the decision he must make. A new multi-criteria decision making with cost criterion analysed at the final stage (MCDM-CCAF) method is developed based on principle of Pareto optimal decisions. It is proposed to exclude the cost criterion from the MCDM analysis and consider it at the final phase of the decision-making process. It is illustrated by example solutions with consideration of cost criterion and without it. It is proposed to apply the invented post-processing method to all MCDM analyses where the cost criterion of analysed variants is considered.
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Riandari, Fristi, Marc Z. Albert, and Stanley S. Rogoff. "MCDM methods to address sustainability challenges, such as climate change, resource management, and social justice." Idea: Future Research 1, no. 1 (2023): 25–38. http://dx.doi.org/10.35335/idea.v1i1.4.
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The novelty of the proposed research lies in its focus on developing and refining MCDM methods to address the complex and multifaceted nature of sustainability challenges, and evaluating the effectiveness and practicality of these methods in real-world decision-making contexts. While previous research has explored the application of MCDM methods to sustainability decision-making, this study aims to advance the field by addressing the following novel aspects: Comprehensive evaluation of MCDM methods: The study aims to comprehensively evaluate the effectiveness and practicality of various MCDM methods in addressing sustainability challenges, including climate change, resource management, and social justice. This evaluation will consider the strengths and limitations of each method, and identify opportunities for improvement. Incorporation of stakeholder values: The study will incorporate stakeholder values into the decision-making process, ensuring that the resulting decisions reflect the diverse perspectives and priorities of all stakeholders. This approach differs from traditional decision-making methods, which often prioritize the perspectives of a select few. Real-world decision-making contexts: The study will evaluate the effectiveness and practicality of MCDM methods in real-world decision-making contexts, providing insights into the challenges and opportunities associated with the implementation of these methods. This will help decision-makers to better understand how to apply MCDM methods to real-world sustainability challenges. The proposed research offers a novel and comprehensive approach to addressing sustainability challenges through the development and application of MCDM methods. By evaluating the effectiveness and practicality of these methods in real-world decision-making contexts, this study aims to provide decision-makers with a more comprehensive and informed approach to sustainability decision-making that reflects the diverse perspectives and priorities of all stakeholders. Future research in the area of MCDM methods to address sustainability challenges could focus on several areas, including: Cross-disciplinary collaborations: Given the complex and multifaceted nature of sustainability challenges, there is a need for cross-disciplinary collaborations between decision-makers, scientists, and stakeholders to develop and implement effective sustainability strategies. Future research could explore how MCDM methods can facilitate these collaborations and promote interdisciplinary dialogue and knowledge sharing. Evaluation of long-term sustainability outcomes: While MCDM methods can help decision-makers to evaluate alternatives based on multiple criteria and stakeholder values, it may be challenging to evaluate the long-term sustainability outcomes of these decisions. Future research could explore how MCDM methods can be used to evaluate the long-term sustainability outcomes of decisions, and how the effectiveness of these methods can be measured over time. Incorporation of ethical considerations: Sustainability decision-making involves ethical considerations related to distributive justice, procedural justice, and environmental ethics. Future research could explore how MCDM methods can incorporate these ethical considerations into the decision-making process to ensure that sustainability decisions are not only efficient and effective but also ethically justifiable. Evaluation of MCDM methods in different decision-making contexts: MCDM methods may be more suitable for certain decision-making contexts than others. Future research could evaluate the effectiveness and practicality of MCDM methods in different decision-making contexts, such as public sector decision-making, corporate decision-making, or community-based decision-making. Development of user-friendly decision support tools: While MCDM methods can be effective in addressing sustainability challenges, they may be challenging to implement in practice. Future research could focus on the development of user-friendly decision support tools that can help decision-makers to implement MCDM methods more easily and effectively. Overall, future research in the area of MCDM methods to address sustainability challenges should focus on advancing the understanding and application of these methods in real-world decision-making contexts. By addressing the challenges and limitations of these methods and developing new approaches to address emerging sustainability challenges, researchers can help decision-makers to make more informed and sustainable decisions for the benefit of society and the environment.
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Sahoo, Sushil Kumar, Bibhuti Bhusan Choudhury, and Prasant Ranjan Dhal. "A Bibliometric Analysis of Material Selection Using MCDM Methods: Trends and Insights." Spectrum of Mechanical Engineering and Operational Research 1, no. 1 (2024): 189–205. http://dx.doi.org/10.31181/smeor11202417.
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The selection of appropriate materials is a critical decision-making process in engineering, impacting both performance and sustainability. Multi-Criteria Decision-Making (MCDM) methods have become increasingly popular for navigating the complex trade-offs involved in material selection. This study presents a comprehensive bibliometric analysis of research on material selection using MCDM methods, covering publications from 2010 to 2024. Using tools like VOSviewer 1.6.20, this analysis identifies key trends, influential authors, prominent institutions, and geographic distribution of research contributions. The findings reveal a significant growth in publications, particularly after 2010, reflecting the expanding recognition of MCDM’s importance in material selection processes. Notable contributors, including key researchers and leading institutions, have shaped the field through high-impact studies. The geographic analysis highlights a strong concentration of research in regions such as Asia and Europe, underscoring their leadership in advancing MCDM methodologies. This paper provides valuable insights into the evolution of material selection research using MCDM, offering a foundation for future studies and applications in engineering and beyond.
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Sahoo, Sushil Kumar, Dragan Pamucar, and Shankha Shubhra Goswami. "A Review of Multi-Criteria Decision-Making Applications to Solve Energy Management Problems From 2010-2025: Current State and Future Research." Spectrum of Decision Making and Applications 2, no. 1 (2025): 219–41. https://doi.org/10.31181/sdmap21202525.
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Energy management is a critical challenge in the global effort to achieve sustainability, improve efficiency, and balance economic and environmental priorities. Multi-Criteria Decision-Making (MCDM) techniques have emerged as powerful tools to address complex and competing criteria in energy systems. This paper reviews the current state of MCDM applications in energy management, focusing on renewable energy systems, energy efficiency, grid management, and policy planning from 2010-2025 using bibliometric analysis. It identifies popular methods such as AHP, TOPSIS, and hybrid models, highlighting their strengths and limitations. The analysis reveals trends, gaps, and challenges, such as handling uncertainty, integrating real-time data, and adapting to dynamic energy environments. Future research directions emphasize leveraging advanced technologies like artificial intelligence, blockchain, and IoT to enhance MCDM models and expanding their application to emerging areas like microgrids and sustainable urban systems. This review provides a comprehensive understanding of the field and outlines a roadmap for advancing MCDM applications in solving energy management problems.
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Alshehri, S. "Multicriteria Decision Making (MCDM) Methods for Ranking Estimation Techniques in Extreme Programming." Engineering, Technology & Applied Science Research 8, no. 3 (2018): 3073–78. http://dx.doi.org/10.48084/etasr.2104.
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It is essential to use multicriteria decision making (MCDM) methods to evaluate human judgments, for decision problems requiring the measuring of tangible and intangible criteria. Among the MCDM techniques, the analytic hierarchical process (AHP) and its extended version, the analytic network process (ANP) are the most powerful methodologies for ranking options and alternatives. They have been utilized by many scientists and researchers in numerous fields, especially for complex engineering problems. Both tools allow leaders to structure their issues numerically utilizing individual judgments. In this article, it is suggested that the MCDM can be useful in agile processes where complicated decisions happen routinely. This paper shows the ranking of the extreme programming (XP) estimation methods using AHP and ANP in educational and industrial environments.
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Voskoglou, Michael Gr. "Grey Multiple-Criteria Decision-Making." International Journal of Grey Systems 4, no. 1 (2024): 5–10. http://dx.doi.org/10.52812/ijgs.88.
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Decision Making (DM) is one of the most important components of human cognition. In particular, the Multiple-Criteria DM (MCDM), is a composite form of DM evaluating options with conflicting goals and choosing the best solution among the existing ones. Following the fuzzy DM criterion of Bellman and Zadeh in 1970, several other methods have been developed by other researchers for DM in fuzzy environments. Here we present a parametric, MCDM method utilizing grey numbers as tools. This method improves an earlier approach of Maji and colleagues in 2002, who used the tabular representation of a soft set as a tool for parametric MCDM in a fuzzy environment. The method is also extended to cover cases of weighted DM and suitable examples are presented illustrating our results.
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Alshehri, Sultan. "Multicriteria Decision Making (MCDM) Methods for Ranking Estimation Techniques in Extreme Programming." Engineering, Technology & Applied Science Research 8, no. 3 (2018): 3073–78. https://doi.org/10.5281/zenodo.1400773.
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It is essential to use multicriteria decision making (MCDM) methods to evaluate human judgments, for decision problems requiring the measuring of tangible and intangible criteria. Among the MCDM techniques, the analytic hierarchical process (AHP) and its extended version, the analytic network process (ANP) are the most powerful methodologies for ranking options and alternatives. They have been utilized by many scientists and researchers in numerous fields, especially for complex engineering problems. Both tools allow leaders to structure their issues numerically utilizing individual judgments. In this article, it is suggested that the MCDM can be useful in agile processes where complicated decisions happen routinely. This paper shows the ranking of the extreme programming (XP) estimation methods using AHP and ANP in educational and industrial environments.
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Safaei Ghadikolaei, Abdolhamid, and Saber Khalili Esbouei. "Integrating Fuzzy AHP and Fuzzy ARAS for evaluating financial performance." Boletim da Sociedade Paranaense de Matemática 32, no. 2 (2014): 163. http://dx.doi.org/10.5269/bspm.v32i2.21378.
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Multi Criteria Decision Making (MCDM) is an advanced field of Operation Research; recently MCDM methods are efficient and common tools for performance evaluation in many areas such as finance and economy. The aim of this study is to show one of applications of mathematics in real word. This study with considering value based measures and accounting based measures simultaneously, provided a hybrid approach of MCDM methods in fuzzy environment for financial performance evaluation of automotive and parts manufacturing industry of Tehran stock exchange (TSE).for this purpose Fuzzy analytic hierarchy process (FAHP) is applied to determine the relative important of each criterion, then The companies are ranked according their financial performance by using fuzzy additive ratio assessment (Fuzzy ARAS) method. The finding of this study showed effective of this approach in evaluating financial performance.
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Hagag, Asmaa M., Laila S. Yousef, and Tamer F. Abdelmaguid. "Multi-Criteria Decision-Making for Machine Selection in Manufacturing and Construction: Recent Trends." Mathematics 11, no. 3 (2023): 631. http://dx.doi.org/10.3390/math11030631.
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As the number of alternative machines has increased and their technology has been continuously developed, the machine selection problem has attracted many researchers. This article reviews recent developments in applying multi-criteria decision-making (MCDM) methods for selecting machines in the manufacturing and construction industries. Selected articles are classified according to the application area and the applied MCDM method. By focusing on the last five years, this paper identifies recent trends in developing and using these methods. Results suggest that there has been a noticeable growth in the utilization of MCDM techniques for machine selection problems in both sectors. It is also noted that several decision-support tools and methods have been developed and successfully applied during this period. Accordingly, needs and directions for future research are discussed.
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Yazdani-Chamzini, Abdolreza, Mohammad Majid Fouladgar, Edmundas Kazimieras Zavadskas, and S. Hamzeh Haji Moini. "SELECTING THE OPTIMAL RENEWABLE ENERGY USING MULTI CRITERIA DECISION MAKING." Journal of Business Economics and Management 14, no. 5 (2013): 957–78. http://dx.doi.org/10.3846/16111699.2013.766257.
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Renewable energies are well-known as one of the most important energy resources not only due to limited other energy resources, but also due to environmental problems associated with air pollutants and greenhouse gas emissions. Renewable energy project selection is a multi actors and sophisticated problem because it is a need to incorporate social, economic, technological, and environmental considerations. Multi criteria decision making (MCDM) methods are powerful tools to evaluate and rank the alternatives among a pool of alternatives and select the best one. COPRAS (COmplex PRoportional ASsessment) is an MCDM technique which determines the best alternative by calculating the ratio to the ideal solution and the negative ideal solution. On the other hand, analytical hierarchy process (AHP) is widely used in order to calculate the importance weights of evaluation criteria. In this paper an integrated COPRAS-AHP methodology is proposed to select the best renewable energy project. In order to validate the output of the proposed model, the model is compared with five MCDM tools. The results of this paper demonstrate the capability and effectiveness of the proposed model in selecting the most appropriate renewable energy option among the existing alternatives.
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Fu, Hsin-Pin, Tien-Hsiang Chang, Cheng-Yuan Ku, Tsung-Sheng Chang, and Cheng-Hsin Huang. "The critical success factors affecting the adoption of inter-organization systems by SMEs." Journal of Business & Industrial Marketing 29, no. 5 (2014): 400–416. http://dx.doi.org/10.1108/jbim-04-2012-0070.
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Purpose – The purposes of this study were to formulate a hierarchical table of factors that influence adoption of an inter-organization system (IOS) by enterprises and to apply multi-criteria decision-making (MCDM) tools to find the weights of these factors and to objectively identify the critical success factors (CSFs) for the adoption of IOSs by small- and medium-sized enterprises (SMEs). Design/methodology/approach – This study first used a literature review to collect the factors that affect an enterprise’s adoption of an IOS and then constructed a three-level hierarchical table of these factors, based on a technology – organization – environment framework. Fuzzy analytic hierarchy processing was used, based on the returned questionnaires, to determine the weights of the factors. The concept of VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) acceptable advantage was used to objectively identify the CSFs of SMEs that have adopted an IOS. Findings – This study identifies six CSFs of SMEs that have adopted an IOS: industry knowledge and experience, the degree of application of information technology within the industry, system safety, the organizational infrastructure, customer relationships and ease of use. In addition, four findings are proposed. Practical implications – The work has studied, in depth, the factors that influence the adoption of an IOS by SMEs and identified four practice implications that provide a useful guideline for SMEs when they plan to adopt an IOS. Originality/value – The identification of CSFs is also an MCDM problem. However, very few previous articles have used MCDM tools to identify the CSFs. This study adopted MCDM tools to objectively identify these CSFs and determine their appropriate weights. The results can help the managers of SMEs allocate their resources, according to the weighting of these CSFs, when they are making plans to adopt an IOS.
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Pavlovskis, M., M. Chizhova, J. Hindmarch, and M. Hess. "APPLICATION OF MULTI-CRITERIA DECISION MAKING FOR THE SELECTION OF SENSING TOOLS FOR HISTORICAL GRAVESTONES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B2-2020 (August 14, 2020): 1435–42. http://dx.doi.org/10.5194/isprs-archives-xliii-b2-2020-1435-2020.
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Abstract. This paper describes a feasibility study for the digitisation of gravestones, specifically Jewish gravestones, alongside an implementation of Multi-Criteria Decision Making. MCDM methods are common in other contexts, and have been used to address issues particular to design, organisation and management of large-scale construction and engineering projects. They are, however, novel in the context of cultural heritage. This paper will examine the potentials of non-contact sensor technologies (including photogrammetry via Structure from Motion, structured light scanning and terrestrial laser scanning) to record, model and archive the stones and their inscriptions. The various methodologies will be assessed against set criteria, specifically speed, resolution, readability and scalability for mass recording, from MCDM including criteria given by humanities scholars in the field of history, theology and Jewish studies.
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Goswami, Shankha Shubhra, Dhiren Kumar Behera, Asif Afzal, et al. "Analysis of a Robot Selection Problem Using Two Newly Developed Hybrid MCDM Models of TOPSIS-ARAS and COPRAS-ARAS." Symmetry 13, no. 8 (2021): 1331. http://dx.doi.org/10.3390/sym13081331.
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Traditional Multi-Criteria Decision Making (MCDM) methods have now become outdated; therefore, most researchers are focusing on more robust hybrid MCDM models that combine two or more MCDM techniques to address decision-making problems. The authors attempted to create two novel hybrid MCDM systems in this paper by integrating Additive Ratio ASsessment (ARAS) with Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Complex PRoportional ASsessment (COPRAS). To demonstrate the ability and effectiveness of these two hybrid models i.e., TOPSIS-ARAS and COPRAS-ARAS were applied to solve a real-time robot selection problem with 12 alternative robots and five selection criteria, while evaluating the parametric importance using the CRiteria Importance Through Inter criteria Correlation (CRITIC) objective weighting estimation tool. The rankings of the robot alternatives gained from these two hybrid models were also compared to the obtained results from eight other solo MCDM tools. Although the rankings by the applied methods slightly differ from each other, the final outcomes from all of the adopted techniques are consistent enough to suggest that robot 12 is the best choice followed by robot 11, and robot 4 is the worst one among these 12 alternatives. Spearman Correlation Coefficient (SCC) also reveals that the proposed rankings derived from various methods have a strong ranking relationship with one another. Finally, sensitivity analysis was performed to investigate the effects of weight variation and to validate the robustness of the implemented MCDM approaches.
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Ulker, Birol, and Bülent Sezen. "A fuzzy based self-check capable computerized MCDM aid tool." Kybernetes 43, no. 5 (2014): 797–816. http://dx.doi.org/10.1108/k-03-2013-0046.
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Purpose – The purpose of this paper is to determine as to develop a fuzzy multi-criteria decision-making (MCDM) algorithm with self-check capability that can solve any manufacturing company's printed circuit boards (PCB) design computer aided design (CAD) tool selection problem and to implement it. Design/methodology/approach – An algorithm that consists of two sub-algorithms that use same inputs and alternative pool is developed, thus self-check capability is introduced. The first sub-algorithm designed as an integration of fuzzy AHP and TOPSIS, where the second sub-algorithm composes of fuzzy analytic network process and TOPSIS. Fuzzy set theory and linguistic variables were utilized to handle uncertainty and usage of verbal expressions, respectively. MATLAB programming language was used for the implementation. The used MCDM methods’ and fuzzy set theory's explanations are given along with the literature review prior to real life application of the developed algorithm. Findings – A MCDM algorithm with self-check capability is introduced. Moreover, a practical decision aid tool is generated for the usage of the manufacturing companies that are related with PCB design. Practical implications – A practical computerized MCDM aid tool is generated. Using the tool let the manufacturers, i.e. high-tech device manufacturers, evaluate available PCB CAD design tools with respect to tangible and intangible criteria, and obtain a reliable result. Originality/value – Self-check capability is incorporated into the decision process. Along with this capability, although the decision-making process takes place in a fuzzy environment, result of the algorithm becomes more reliable than the ones deprived of this characteristic. Furthermore, a practical computerized MCDM aid tool is generated.
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Csiszár, Orsolya, Gábor Csiszár, and József Dombi. "How to implement MCDM tools and continuous logic into neural computation?" Knowledge-Based Systems 210 (December 2020): 106530. http://dx.doi.org/10.1016/j.knosys.2020.106530.
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Shaverdi, Meysam, Mahsa Akbari, and Saeed Fallah Tafti. "Combining Fuzzy MCDM with BSC Approach in Performance Evaluation of Iranian Private Banking Sector." Advances in Fuzzy Systems 2011 (2011): 1–12. http://dx.doi.org/10.1155/2011/148712.
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The objective of this study is to construct an approach based on multiple criteria decision making (MCDM) and balanced scorecard (BSC) for evaluating performance for three nongovernmental Iranian's banks. Following the literature relating to banking performance and BSC concepts, experts and managers select 21 indexes for evaluation. Furthermore, fuzzy analytic hierarchy process (FAHP) calculated the relative weights of each chosen index in order to tolerate vagueness and ambiguity of information, and three MCDM analytical tools (TOPSIS, VIKOR, and ELECTRE) were adopted to rank the banking performance. The results indicate that a customer “” has the most significant BSC perspectives and the customer satisfaction “” is the most major index in banking sector. This proposed fuzzy MCDM method combined with BSC approach is a comprehensive and up-to-date model that can be a useful and effective assessment tool.
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Ebhomien, L. E., O. Obarisiagbon, H. Omorogbe, and I. F. Omobude. "The Need for the Inclusion of Multi-Criteria Decision Analysis in Architectural Design Education in Nigeria." Nigerian Journal of Environmental Sciences and Technology 1, no. 1 (2017): 131–35. http://dx.doi.org/10.36263/nijest.2017.01.0008.
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The inclusion of multi-criteria decision making (MCDM) methodologies as functional design tools in architecture has become a staple feature in architectural studies and research work. The trend while necessitated by challenges presented by the actualities involved in architectural practice, takes for granted the acceptability and knowledgeability of the built environment professional. This study highlights the fact that for MCDM to find general adoption and to provide its benefit in widespread solutions, the architect to whom these methodologies are advanced, should have an introduction to these approaches, formally at the educational level. Therefore, this paper evaluates the need for the inclusion of MCDM in architectural curriculum in Nigerian schools of architecture. The views of practicing professional architects, faculty members and students, were quantitatively and qualitatively analysed in a cross-sectional survey administered via questionnaires. A total of 54 respondents were evaluated, with findings of the study, indicating the novelty of MCDM and a general consensus for its introduction into the architectural curriculum, but varied opinions at what stage it should be introduced: 64% (undergraduate level); 26% (Masters’ level) and 10% (postmasters’ level). Consequently, the study recommended that MCDM be introduced at the undergraduate level, because students would be better situated intellectually to apply, modify and diversify the methodology in architectural problem modelling in the long run.
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Abdulaal, Reda M. S., and Omer A. Bafail. "Two New Approaches (RAMS-RATMI) in Multi-Criteria Decision-Making Tactics." Journal of Mathematics 2022 (September 27, 2022): 1–20. http://dx.doi.org/10.1155/2022/6725318.
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When a decision must be made, a tool called multi-criteria decision-making (MCDM) is used to assess and select alternatives among numerous criteria. For a wide variety of complex problems, MCDM methods have demonstrated usefulness in finding the optimal solutions. Despite the abundance of MCDM methods available today, there has been slow progress in developing new methodologies in MCDM in the past decade. In this context, this paper presents new MCDM tools which ranks alternatives based on median similarity (RAMS) between optimal alternatives and other alternatives. RAMS is an extension to the most recently developed technique that used perimeter similarity (RAPS). This paper also introduces a further tool that combines the RAMS method with the multiple criteria ranking by alternative trace (MCRAT) methodology using a majority index and the concept of the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method. This tool is ranking the alternatives based on the trace to median index (RATMI). An illustration of the use of RAMS and RATMI is given through a case study of ranking different materials for the selection of break booster valve body in a vehicle. The validity of the new two techniques was tested against seven well-known MCDM techniques (ARAS, SAW, TOPSIS, COPRAS, VIKOR, WASPAS, and MOORA) using fifteen real problems data taken from the literature. The RATMI technique was more promising than RAPS and RAMS for 87% and 93% of the fifteen difficulties, respectively, according to the results of the correlation coefficient tests between the developed techniques and the selected seven techniques.
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Debojit, Roy, and Mitra Soupayan. "Selection of best scooter model using the fuzzy- AHP MCDM methodology." i-manager’s Journal on Management 16, no. 4 (2022): 31. http://dx.doi.org/10.26634/jmgt.16.4.18917.
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The Multi-Criteria Decision Making (MCDM) is a new and advanced managerial tool for evaluating the best solution at the optimal level. The main purpose of the MCDM tool is to solve complex decision problems where the decision-makers are experiencing lots of conflicts. The decisions are to be made based on the criteria and their relative importance. If the decision that has to be taken have financial and resource involvement, the decision has to be taken very attentively. Selecting the best-suited scooter also involves many complex aspects like design and ergonomics, power output, fuel economy, price, and many other aspects. The objectives of this particular work are to find the best scooter model among four selective alternatives and to study and evaluate various MCDM tools like the Fuzzy-AHP methods, which are vigorously used in solving different complex decision or selection problems based on criteria associated with this problem.
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Gogodze, Joseph. "Revealed Comparative Advantage Method for Solving Multicriteria Decision-making Problems." Foundations of Computing and Decision Sciences 46, no. 1 (2021): 85–96. http://dx.doi.org/10.2478/fcds-2021-0006.
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Abstract This study proposes and analyzes a new method for the post-Pareto analysis of multicriteria decision-making (MCDM) problems: the revealed comparative advantage (RCA) assessment method. An interesting feature of the suggested method is that it uses the solution to a special eigenvalue problem and can be considered an analog/modification in the MCDM context of well-known ranking methods including the authority-hub method, PageRank method, and so on, which have been successfully applied to such fields as economics, bibliometrics, web search design, and so on. For illustrative purposes, this study discusses a particular MCDM problem to demonstrate the practicality of the method. The theoretical considerations and conducted calculations reveal that the RCA assessment method is self-consistent and easily implementable. Moreover, comparisons with well-known tools of an MCDM analysis shows that the results obtained using this method are appropriate and competitive. An important particularity of the RCA assessment method is that it can be useful for decision-makers in the case in which no decision-making authority is available or when the relative importance of various criteria has not been preliminarily evaluated.
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Jamil, Nadia, Rosli Besar, and H. K. Sim. "A Study of Multicriteria Decision Making for Supplier Selection in Automotive Industry." Journal of Industrial Engineering 2013 (March 25, 2013): 1–22. http://dx.doi.org/10.1155/2013/841584.
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This paper is designed to present the effectiveness of group multicriteria decision making in automotive manufacturing company focusing on the selection of suppliers in Malaysia. The process of selecting suppliers is one of the most critical and challenging endeavor in any supply chain management. There are five decision making tools being analyzed in this study, namely, analytical hierarchy process (AHP), fuzzy analytical hierarchy process (FAHP), technique for order performance by similarity to ideal solution (TOPSIS), fuzzy technique for order performance by similarity to ideal solution (FTOPSIS), and fuzzy analytical hierarchy process integrated with fuzzy technique for order performance by similarity to ideal solution (FAHPiFTOPSIS). The scores of ranking among the suppliers in each MCDM tools (AHP, FAHP, TOPSIS, FTOPSIS, and FAHPiFTOPSIS) show significantly comparable variation. Scores of the best supplier is then compared to the lowest supplier for all MCDM tools whereby this reflects that the highest percentage goes to TOPSIS with scoring of 79.37%. On the contrary, FAHPiFTOPSIS demonstrated the lowest score variation of 22.42% which indicates that FAHPiFTOPSIS is able to eliminate biasness in supplier selection process.
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Aldaghi, Tahmineh, and Jan Muzik. "Multicriteria Decision-Making in Diabetes Management and Decision Support: Systematic Review." JMIR Medical Informatics 12 (February 1, 2024): e47701. http://dx.doi.org/10.2196/47701.
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Background Diabetes mellitus prevalence is increasing among adults and children around the world. Diabetes care is complex; examining the diet, type of medication, diabetes recognition, and willingness to use self-management tools are just a few of the challenges faced by diabetes clinicians who should make decisions about them. Making the appropriate decisions will reduce the cost of treatment, decrease the mortality rate of diabetes, and improve the life quality of patients with diabetes. Effective decision-making is within the realm of multicriteria decision-making (MCDM) techniques. Objective The central objective of this study is to evaluate the effectiveness and applicability of MCDM methods and then introduce a novel categorization framework for their use in this field. Methods The literature search was focused on publications from 2003 to 2023. Finally, by applying the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) method, 63 articles were selected and examined. Results The findings reveal that the use of MCDM methods in diabetes research can be categorized into 6 distinct groups: the selection of diabetes medications (19 publications), diabetes diagnosis (12 publications), meal recommendations (8 publications), diabetes management (14 publications), diabetes complication (7 publications), and estimation of diabetes prevalence (3 publications). Conclusions Our review showed a significant portion of the MCDM literature on diabetes. The research highlights the benefits of using MCDM techniques, which are practical and effective for a variety of diabetes challenges.
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Hu, Hongxia, Shouguo Jiang, Shankha Shubhra Goswami, and Yafei Zhao. "Fuzzy Integrated Delphi-ISM-MICMAC Hybrid Multi-Criteria Approach to Optimize the Artificial Intelligence (AI) Factors Influencing Cost Management in Civil Engineering." Information 15, no. 5 (2024): 280. http://dx.doi.org/10.3390/info15050280.
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This research paper presents a comprehensive study on optimizing the critical artificial intelligence (AI) factors influencing cost management in civil engineering projects using a multi-criteria decision-making (MCDM) approach. The problem addressed revolves around the need to effectively manage costs in civil engineering endeavors amidst the growing complexity of projects and the increasing integration of AI technologies. The methodology employed involves the utilization of three MCDM tools, specifically Delphi, interpretive structural modeling (ISM), and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC). A total of 17 AI factors, categorized into eight broad groups, were identified and analyzed. Through the application of different MCDM techniques, the relative importance and interrelationships among these factors were determined. The key findings reveal the critical role of certain AI factors, such as risk mitigation and cost components, in optimizing the cost management processes. Moreover, the hierarchical structure generated through ISM and the influential factors identified via MICMAC provide insights for prioritizing strategic interventions. The implications of this study extend to informing decision-makers in the civil engineering domain about effective strategies for leveraging AI in their cost management practices. By adopting a systematic MCDM approach, stakeholders can enhance project outcomes while optimizing resource allocation and mitigating financial risks.
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Şenel, Güzide. "An Innovative Algorithm Based on Octahedron Sets via Multi-Criteria Decision Making." Symmetry 16, no. 9 (2024): 1107. http://dx.doi.org/10.3390/sym16091107.
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Octahedron sets, which extend beyond the previously defined fuzzy set and soft set concepts to address uncertainty, represent a hybrid set theory that incorporates three distinct systems: interval-valued fuzzy sets, intuitionistic fuzzy sets, and traditional fuzzy set components. This comprehensive set theory is designed to express all information provided by decision makers as interval-valued intuitionistic fuzzy decision matrices, addressing a broader range of demands than conventional fuzzy decision-making methods. Multi-criteria decision-making (MCDM) methods are essential tools for analyzing and evaluating alternatives across multiple dimensions, enabling informed decision making aligned with strategic objectives. In this study, we applied MCDM methods to octahedron sets for the first time, optimizing decision results by considering various constraints and preferences. By employing an MCDM algorithm, this study demonstrated how the integration of MCDM into octahedron sets can significantly enhance decision-making processes. The algorithm allowed for the systematic evaluation of alternatives, showcasing the practical utility and effectiveness of octahedron sets in real-world scenarios. This approach was validated through influential examples, underscoring the value of algorithms in leveraging the full potential of octahedron sets. Furthermore, the application of MCDM to octahedron sets revealed that this hybrid structure could handle a wider range of decision-making problems more effectively than traditional fuzzy set approaches. This study not only highlights the theoretical advancements brought by octahedron sets but also provides practical evidence of their application, proving their importance and usefulness in complex decision-making environments. Overall, the integration of octahedron sets and MCDM methods marks a significant step forward in decision science, offering a robust framework for addressing uncertainty and optimizing decision outcomes. This research paves the way for future studies to explore the full capabilities of octahedron sets, potentially transforming decision-making practices across various fields.
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Mukhanbetkaliyev, D., and V. Serbin. "MULTI-CRITERIA DECISION-MAKING MODEL FOR SELECTING SUPPLIERS' OFFERS." Deutsche internationale Zeitschrift für zeitgenössische Wissenschaft 75 (March 6, 2024): 57–59. https://doi.org/10.5281/zenodo.10788713.
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Multi-criteria decision-making (MCDM) is one of the main decision-making problems which aims to determine the best alternative by considering more than one criterion in the selection process. MCDM has manifold tools and methods that can be applied in different fields from finance to engineering design. This scientific article presented a multi-criteria decision-making model for selecting supplier proposals. The developed model is based on the analysis of several criteria that may influence the choice of supplier. The criteria were classified based on their impact on the organization's business processes. The study showed that the model allows accurate and reliable decisions in this area.
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Haghnazar Koochaksaraei, Roozbeh, Frederico Gadelha Guimarães, Babak Hamidzadeh, and Sarfaraz Hashemkhani Zolfani. "Visualization Method for Decision-Making: A Case Study in Bibliometric Analysis." Mathematics 9, no. 9 (2021): 940. http://dx.doi.org/10.3390/math9090940.
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Data and information visualization have drawn an increasingly wide range of interest from several academic fields and industries. Concurrently, exploring a huge set of data to support feasible decisions needs an organized method of Multi-Criteria Decision Making (MCDM). The dramatic increasing of data producing during the past decade makes visualization necessary as a presentation layer on the top of MCDM process. This study aims to propose an integrated strategy to rank the alternatives in the dataset, by combining data, MCDM methods, and visualization layers. In fact, the well designed combination of Information Visualization and MCDM provides a more user-friendly approach than the traditional methods. We investigate a case study in bibliometric analyses, which have become an important dimension and tool for evaluating the impact and performance of researchers, departments, and universities. Hence, finding the best and most reliable papers, authors, and publishers considering diverse criteria is one of the important challenges in science world. Therefore, this text is presenting a new strategy on the bibliometric dataset as a case study and it demonstrates that this strategy can be more meaningful for the end users than the current tools. Finally, the presented simulations illustrate the performance and utilization of this combination. In other words, the researchers of this study could design and implement a tool that overcomes the biggest challenges of data analyzing and ranking via a combination of MCDM and visualization methodologies that can provide a tremendous amount of insight and information from a massive dataset in an efficient way.
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Sharma, Sunil Kumar. "A Bhattacharyya Triangular intuitionistic fuzzy sets with a Owa operator-based decision making for optimal portfolio selection in Saudi exchange." AIMS Mathematics 9, no. 10 (2024): 27247–71. http://dx.doi.org/10.3934/math.20241324.
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<p>The capital market in Saudi Arabia is fast growing. Assurance of an informed decision while investing in the Saudi Stock Exchange is critical. There has also been an increased quest for advanced decision-making tools due to complexities in selecting a given portfolio, which remains a critical issue of concern among investors in the face of modern investment environment challenges. The research paper offered shall deliver an innovative MCDM technique through which an MCDM model shall be developed in the Saudi Stock Exchange. This MCDM model uses BTIFS with an OWA operator. A novelty of the proposed study is identifying the optimal weight that will be obtained through a newly developed optimization technique known as TFOA. TFOA is a hybrid methodology that brings on board the strengths of DMOA, MPA, and EO for a more precise and efficient calculation of the ideal weights in the portfolio selection process. This would improve the adaptability and effectiveness of the suggested MCDM structure. The effectiveness of the approach is established by comparative analysis with the already existing methods of MCDM, which proves it superior for the optimization of investment portfolios. Sensitivity analysis also conducted to evaluate the strength and dependability of the suggested method. The ranking of weighted portfolios by the ELECTRE method is also, which more establishes the applicability of BTIFS-OWA in real life. The results indicate that the BTIFS-OWA approach along with the TFOA for determining optimal weights provides significant improvements in decision-making accuracy and portfolio optimization compared to traditional methods.</p>
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Ghosh, Arijit, Neha Ghorui, Sankar Prasad Mondal, et al. "Application of Hexagonal Fuzzy MCDM Methodology for Site Selection of Electric Vehicle Charging Station." Mathematics 9, no. 4 (2021): 393. http://dx.doi.org/10.3390/math9040393.
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In this paper, the application of hexagonal fuzzy multiple-criteria decision-making (MCDM) methodology for the site selection of electric vehicle charging stations is considered. In this regard, four factors and thirteen sub-factors have been taken into consideration for E-vehicle charging site selection. In this research, the geographic information system (GIS) has been incorporated with MCDM techniques. The fuzzy analytic hierarchy process (FAHP) is used to obtain a fuzzy weight of factors and sub-factors. MCDM tools fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS) and fuzzy complex proportional assessment (FCOPRAS) have been used to rank the selected sites. A centroid-based method for defuzzification and distance measure between two hexagonal fuzzy numbers (HFN) has been developed for this paper. A practical example in Howrah, India, is considered to show the applicability and usefulness of the model. The results depict the suitability of the proposed research. Comparative and sensitivity analyses have been demonstrated to check the reliability, robustness and effectiveness of the proposed method.
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Ayan, Büşra, Seda Abacıoğlu, and Marcio Pereira Basilio. "A Comprehensive Review of the Novel Weighting Methods for Multi-Criteria Decision-Making." Information 14, no. 5 (2023): 285. http://dx.doi.org/10.3390/info14050285.
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In the realm of multi-criteria decision-making (MCDM) problems, the selection of a weighting method holds a critical role. Researchers from diverse fields have consistently employed MCDM techniques, utilizing both traditional and novel methods to enhance the discipline. Acknowledging the significance of staying abreast of such methodological developments, this study endeavors to contribute to the field through a comprehensive review of several novel weighting-based methods: CILOS, IDOCRIW, FUCOM, LBWA, SAPEVO-M, and MEREC. Each method is scrutinized in terms of its characteristics and steps while also drawing upon publications extracted from the Web of Science (WoS) and Scopus databases. Through bibliometric and content analyses, this study delves into the trend, research components (sources, authors, countries, and affiliations), application areas, fuzzy implementations, hybrid studies (use of other weighting and/or ranking methods), and application tools for these methods. The findings of this review offer an insightful portrayal of the applications of each novel weighting method, thereby contributing valuable knowledge for researchers and practitioners within the field of MCDM.
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Kumar, Rahul, and Dragan Pamucar. "A Comprehensive and Systematic Review of Multi-Criteria Decision-Making (MCDM) Methods to Solve Decision-Making Problems: Two Decades from 2004 to 2024." Spectrum of Decision Making and Applications 2, no. 1 (2025): 178–97. https://doi.org/10.31181/sdmap21202524.
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Decision-making in complex, multifaceted scenarios has become increasingly critical across diverse sectors, necessitating robust frameworks like Multi-Criteria Decision-Making (MCDM). Over the past two decades (2004–2024), MCDM has transformed from foundational methods like AHP and TOPSIS into dynamic hybrid models integrating artificial intelligence, fuzzy logic, and machine learning. Despite significant strides, the field faces challenges in addressing geographic disparities, underexplored domains and adapting to emerging global needs. This study provides a comprehensive review of MCDM's evolution, consolidating insights from 3,655 peer-reviewed articles sourced through Dimensions.ai and analyzed using bibliometric tools like VOSviewer. The research identifies publication trends, leading contributors, thematic clusters, and collaborative networks while pinpointing gaps and opportunities for future exploration. These Key findings highlight exponential growth in MCDM applications, particularly in sustainable energy, urban planning, and healthcare optimization. These advancements align with global priorities, including the United Nations Sustainable Development Goals (SDGs) such as clean energy, climate action, and sustainable cities. However, critical gaps remain in addressing issues like poverty alleviation, gender equity, and biodiversity conservation, emphasizing the need for broader interdisciplinary applications. This review concludes that MCDM's potential lies in embracing inclusivity, advancing into emerging technologies like blockchain and the metaverse, and fostering collaboration across underrepresented regions and domains. By harnessing real-time data, immersive simulations, and secure decision-making platforms, MCDM can redefine how global challenges are addressed.
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Goyal, Pooja, and Sukhvinder Singh Deora. "Cloud service ranking with an integration of k-means algorithm and decision-making trail and evaluation laboratory approach." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 2 (2024): 1816. http://dx.doi.org/10.11591/ijece.v14i2.pp1816-1824.
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The present research focuses on ranking cloud services by using the k-means algorithm with multi-criteria decision-making (MCDM) approaches that are the prime factor in the decision-making process and have been used to choose cloud services. The tools offered by MCDM can solve almost any decision-making problem. When faced with a selection challenge in the cloud environment, the trusted party would need to weigh the client’s choice against a predetermined list of criteria. There is a wide range of approaches to evaluating the quality of cloud services. The deep learning model has been considered a branch of artificial intelligence that assesses datasets to perform training and testing and makes decisions accordingly. This paper presents a concise overview of MCDM approaches and discusses some of the most commonly used MCDM methods. Also, a model based on deep learning with the k-means algorithm based decision-making trial and evaluation laboratory (kDE-MATEL) and analytic network process (ANP) is proposed as k-means algorithm based decision-making trial and evaluation laboratory with analytic network process (kD-ANP) for selecting cloud services. The proposed model uses the k-means algorithm and gives different levels of priority and weight to a set of criteria. A traditional model is also compared with a proposed model to reflect the efficiency of the proposed approach.
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Goyal, Pooja, and Sukhvinder Singh Deora. "Cloud service ranking with an integration of k-means algorithm and decision-making trail and evaluation laboratory approach." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 2 (2024): 1816–24. https://doi.org/10.11591/ijece.v14i2.pp1816-1824.
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The present research focuses on ranking cloud services by using the k-means algorithm with multi-criteria decision-making (MCDM) approaches that are the prime factor in the decision-making process and have been used to choose cloud services. The tools offered by MCDM can solve almost any decision-making problem. When faced with a selection challenge in the cloud environment, the trusted party would need to weigh the client’s choice against a predetermined list of criteria. There is a wide range of approaches to evaluating the quality of cloud services. The deep learning model has been considered a branch of artificial intelligence that assesses datasets to perform training and testing and makes decisions accordingly. This paper presents a concise overview of MCDM approaches and discusses some of the most commonly used MCDM methods. Also, a model based on deep learning with the k-means algorithm based decision-making trial and evaluation laboratory (kDE-MATEL) and analytic network process (ANP) is proposed as k-means algorithm based decision-making trial and evaluation laboratory with analytic network process (kD-ANP) for selecting cloud services. The proposed model uses the k-means algorithm and gives different levels of priority and weight to a set of criteria. A traditional model is also compared with a proposed model to reflect the efficiency of the proposed approach.
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Farooq, Fozia Bashir, Sobia Sultana, Nouf Abdulrahman Alqahtani, and Muhammad Imran. "Optimization of HIV drugs through MCDM technique Analytic Hierarchy Process(AHP)." PLOS ONE 20, no. 1 (2025): e0316617. https://doi.org/10.1371/journal.pone.0316617.
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Topological indices are crucial tools for predicting the physicochemical and biological features of different drugs. They are numerical values obtained from the structure of chemical molecules. These indices, particularly the degree-based TIs are a useful tools for evaluating the connection between a compound’s structure and its attributes. This study addresses the research problemof how to optimize drug design for HIV treatment using degree-based topological indices. The need for safer and more effective medicines for HIV is further emphasized by the advent of drug resistance and severe negative effects from current therapies. Employing degree-based graph invariants, the study investigates 13 HIV drugs by applying a quantitative structure-property relationship (QSPR) technique to associate their molecular structures with their physical properties. HIV drugs are ranked using the Analytic Hierarchy Process (AHP) according to specific parameters. The findings of the study demonstrate how well these approaches can determine the most effective possible drug combinations and designs, offering insightful information in developing improved HIV treatments.
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Senthilkannan, N., and R. Parameshwaran. "Integrated approach for product optimisation in a rolling mill using fuzzy MCDM tools." International Journal of Additive and Subtractive Materials Manufacturing 2, no. 1 (2018): 25. http://dx.doi.org/10.1504/ijasmm.2018.093272.
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R, Parameshwaran, and SenthilKannan N. "Integrated approach for Product Optimization in a Rolling Mill using Fuzzy MCDM Tools." International Journal of Additive and Subtractive Materials Manufacturing 2, no. 1 (2018): 1. http://dx.doi.org/10.1504/ijasmm.2018.10013374.
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