Multiple Criteria Decision Making, 2nd Edition

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Fuzzy Sets, Systems and Decision Making".

Deadline for manuscript submissions: 31 March 2025 | Viewed by 13243

Special Issue Editors


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Guest Editor
Department of Law, Business Management faculty, Vilnius Gediminas Technical University, LT-10223 Vilnius, Lithuania
Interests: operations research; optimization and decision analysis; multicriteria decision making; MCDM; multiple-criteria optimization; multiattribute decision making (MADM); multiobjective optimization (MODM); approximations; mathematics for decision making; decision support systems; evaluation sustainable development; civil engineering; management; knowledge management; game theory and economical computing; finance engineering; algorithms and software engineering; energy; fuzzy set theory; negotiations; the consensus in groups
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Laboratory of Operations Research, Institute of Sustainable Construction, Faculty of Civil Engineering, Vilnius Gediminas Technical University, Saulėtekio al. 11, LT-10223 Vilnius, Lithuania
Interests: operations research; optimization and decision analysis; multicriteria decision making; MCDM; multiple-criteria optimization; multiattribute decision making (MADM); multiobjective optimization (MODM); approximations; mathematics for decision making; decision support systems; evaluation sustainable development; civil engineering; management; knowledge management; game theory and economical computing; finance engineering; algorithms and software engineering; energy; fuzzy set theory; negotiations; the consensus in groups
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Decision making is one of the most critical topics in various areas of human activity, and the field involves  making the right decisions to reach the end goal. Decision makers over the past few decades have successfully used multicriteria decision-making (MCDM) approaches to solve complex decision-making problems in a variety of fields, such as economics, finance, logistics, environmental remediation, business, engineering, medicine, law, and more. Decision makers need MCDM tools that help to balance conflicting goals with multiple choices and limited resources and time for decision makers to match conflicting goals.

Therefore, the use of the MCDM methods for solving problems in different fields is prevalent and helps in making significant decisions. MCDM is an effective systematic and quantitative way to deal with issues in the presence of several alternatives and several usually different criteria. Decision making regarding very complex problems, including business-related decisions and real-life decisions, requires an appropriate and reliable decision-support system. Optimization may be considered a decision-making process to get the most out of available resources to obtain the best possible results. Many real-world problems are multifaceted or multiattribute problems, which naturally involve multiple competing goals that need to be optimized at the same time within certain constraints or by choosing from the available discrete alternatives. In contrast to single-goal optimization, solutions to multiobjective and multiattribute problems correspond to a set of solutions with trade-offs, each expressing a peculiar trade-off between different goals or attributes. Optimization can be considered a decision-making process to maximize the effectiveness of the available resources used to achieve the best results possible.

 Considering, planning, and appropriate decision making require the use of analytical methods that examine trade-offs, consider multiple scientific, political, economic, ecological and social dimensions, and reduce possible conflicts in an optimizing framework. MCDM techniques fall into two major groups. The first group is discrete MCDM, including multiattribute utility theory (MAUT), analytic hierarchy process/analytic network process (AHP/ANP), and outranking methods, where the decision maker has to evaluate a finite set of alternatives to a) select the best option, b) rank alternatives from the best to worst, and c) classify alternatives into predefined classes or the described options (i.e., multiattribute decision-making (MADM) methods). The second is continuous MCDM, including multiobjective programming and goal programming, where there is an infinite set of alternatives (i.e., multiobjective decision-making (MODM) methods).

MCDM approaches are considered the established methods to aid decision makers in taking suitable decisions, and their applications are growing in popularity in many fields, including but are not limited to business management, logistics, supply chains, energy, urban development, waste management, and others. In decision-making theories and in business practice, decision makers encounter many imprecise concepts. Imprecise data are the premises which serve the specification of economic models and, consequently, the decision-making process. All this requires the utilization of the vague interference rule. In the second half of the 20th century, we witnessed the development of the behavioral economy. The world of economic concepts and models became even more imprecise. In addition, design, planning, and operations management rely on mathematical models, the complexity of which depends on the detail of models and complexity/characteristics of the problem they represent. It is thus no surprise that with the ever-increasing complexity of the issues, optimization comes with an inherent facet of uncertainty conveyed in different formal ways and calls for innovative approaches to produce optimal and interpretable solutions. Today’s real-world problems involve multiple data sets, some precise or objective and some uncertain or subjective. Many decision problems manage linguistic information assessed through several ordered qualitative scales. In these contexts, the main question arising is how to aggregate this qualitative information. This Special Issue welcomes MCDM procedures that rank a set of alternatives assessed using a specific non-uniform ordered qualitative scale for each criterion. Therefore, ordinal models to manage the ordinal degree of proximity from different ordered qualitative sizes are essential to this issue. Moreover, decision makers often make decisions in the face of the unknown.

A wide range of statistical and nonstatistical decision-making techniques have been proposed in the literature to model complex business processes. Unfortunately, decision making by humans is often suboptimal in ways that can be reliably predicted. Fuzzy set theory laid the foundations for significant modeling uncertainty, vagueness, and imprecision. The method of fuzzy sets noted substantial progress in economics in both theoretical and practical studies. MCDM has considerably expanded beyond classical and formal methodologies and has also involved intuitive and informal processes. Therefore, in addition to conventional MCDM methods, this Special Issue also welcomes their integration with uncertainty theory, such as fuzzy sets, rough sets, neutrosophic sets, etc.

Different mathematical models of real-life multicriteria optimization problems can be applied to various uncertain frameworks, with particular emphasis on real-life optimization problems. Neutrosophic logic, set, probability, statistics, and others are respectively generalizations of fuzzy and intuitionistic fuzzy logic and set, classical and imprecise probability, classical statistics, and others. Furthermore, the process industry seeks not only to minimize cost but also to minimize adverse environmental and social impacts. On the other hand, to give an appropriate response to the new challenges raised, the decision-making process can be done by applying different methods and tools, as well as using different objectives. In real-life problems, the formulation of decision-making problems and the application of optimization techniques to support decisions are particularly complex, and a wide range of optimization techniques and methodologies are used to minimize risks or improve quality in making concomitant decisions. The importance of strategic behavior in the human and social world is increasingly recognized in theory and practice. As a result, multicriteria optimization models and applications have emerged as a fundamental tool in pure and applied research. Multicriteria optimization models and applications strongly support decision-making processes in an interactive environment. They draw on mathematics, economics, statistics, engineering, biology, political science, operations research, and other subjects. A multioptimization occurs when multiple criteria considered by a decision maker are evaluated with mathematical optimization problems involving more than one objective function to be optimized simultaneously. The decision maker finds a set of objectives in a situation in which each goal is possibly conflicting, possibly equally important, or perhaps overlapping. The problem is then to determine the trade-off between objectives to support the decision-making process. Additionally, a sensitivity analysis should be done to validate/analyze the influence of uncertainty regarding decision making.

In this Special Issue, researchers from academia and industry are invited to submit papers that explore aspects of multiobjective or multiattribute modeling and optimization in a crisp or uncertain environment. The Issue will elaborate on the state-of-the-art case studies in selected areas of application related to sustainable development decision support. Analytical models, empirical studies, and case-based studies are all welcome, as long as the research work provides new insights and implications for the practice of decision making.

In recent years, new mathematical developments have been applied in the context of financial economics. Thus, a relevant challenge is to provide a bridge between new mathematical tools on the one hand and economics and finance issues on the other.

Articles are welcome on this issue where systemic solutions in practical decision making that bring economic, social, and environmental benefits are offered through a variety of methodologies and tools (e.g., information technologies and multiple-criteria decision-making methods). Articles that propose new methods dealing with multifaceted issues are also welcome.

Since the pioneering paper of Zadeh, many extensions of the fuzzy set theory with practical applications in different areas have also been proposed, including intuitionistic fuzzy sets, interval-valued fuzzy sets, interval-valued intuitionistic fuzzy sets, rough sets, bipolar fuzzy sets, grey sets, hesitant fuzzy sets, fuzzy numbers, and fuzzy oriented sets, among others. The multivalued logic and the lattice are the theoretical background of fuzzy set theory. MCDM methods for handling imprecision and vagueness in real decision-making problems are used in several different areas. The fuzzy set theory makes it possible to capture uncertainty, imprecision, inaccurate definitions of decision problems and, as a consequence, fuzzing the issue.

As Guest Editors, we invite original research papers for this Special Issue that report on the state-of-the-art and recent advancements in multicriteria decision making using the fuzzy or vague determined environment to computing, group decision-making problems, pattern recognition, information processing, and many other practical achievements.

The objective of this Special Issue is to gather a collection of papers reflecting the latest developments in practical applications of the MCDM mathematical tools and the latest developments in the mathematical programming methods of operations research for multicriteria optimization for different fields of multicriteria optimization approaches, models, applications and techniques. The use of some factor models to manage potential risks and other applications in economic theory and modeling are also of interest.

The scope of this Issue covers MCDM in a broad sense, focusing on recent advances in both discrete and continuous techniques and significant applications in different fields.

This Special Issue focuses on the science and art of multicriteria decisions, especially in multidisciplinary settings. We expect to publish high-quality papers in the categories of discovery, integration, application, and teaching of multicriteria decisions.

We invite authors to submit original research and review articles which give a more in-depth insight into the applications of MCDM theories in real-life problem-solving.

We hope that this Special Issue will stimulate both theoretical and applied research on MCDM and related fields. It is impossible in this short editorial to provide a more comprehensive description of all potential articles in this Special Issue.

We invite authors to submit original research articles which propose novel MCDM optimization models for solving real-life-related problems.

  • Decent work and economic growth.
  • Industry, innovation, and infrastructure.
  • Sustainable development.
  • Responsible resource consumption and production.
  • Climate action.
  • Peace, justice and strong institutions.

The proposed papers should present advanced MCDM systems related to the following directions of quantified decision making:

  • Applications of MCDM.
  • Modeling of MCDM.
  • Decision analysis for sustainable production and consumption.
  • Decision support systems.
  • Discrete and continuous MCDM.
  • Economic diagnosis and forecasting.
  • Fuzziness in MCDM.
  • Granular computing-based multiobjective or multiattribute optimization.
  • Group decision making.
  • Integrated approaches for modeling decision making.
  • Intuitiveness in MCDM.
  • MCDM methodologies.
  • MCDM theories.
  • MCDM in strategic management.
  • MCDM design issues.
  • Multigoal decisions.
  • MODM intelligence problem.
  • Multistage multiobjective or multiattribute problems.
  • MCDM negotiation and group decisions.
  • Neural-network-based multiobjective or multiattribute optimization.
  • Risk management.
  • Soft-computing techniques for MCDM.
  • Survey and theoretical articles, as well as application papers.
  • The development of MCDM Methods capable of capturing sustainability.
  • The development of MCDM methods capable of capturing sustainability and fuzziness (uncertainty, imprecision and inaccurate definition) of the decision problem.
  • Tools for multicriteria decisions.

We are motivated by the overriding aim to indicate the connections between MCDM systems and real-life problems.

Prof. Violeta Šniokienė
Prof. Dr. Zenonas Turskis
Guest Editors

Manuscript Submission Information

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

Keywords

  • decent work and economic growth
  • industry, innovation, and infrastructure
  • sustainable development
  • responsible resource consumption and production
  • climate action
  • applications of MCDM
  • modeling of MCDM
  • decision analysis for sustainable production and consumption
  • decision support systems
  • discrete and continuous MCDM
  • economic diagnosis and forecasting
  • fuzziness in MCDM
  • granular computing-based multiobjective or multiattribute optimization
  • group decision making
  • integrated approaches for modeling decision making
  • intuitiveness in MCDM
  • MCDM methodologies
  • MCDM theories
  • MCDM in strategic management
  • MCDM design issues
  • multigoal decisions
  • MODM intelligence problem
  • multistage multiobjective or multiattribute problems
  • MCDM negotiation and group decisions
  • neural-network-based multiobjective or multiattribute optimization
  • risk management
  • soft-computing techniques for MCDM
  • survey and theoretical articles, as well as application papers
  • the development of MCDM Methods capable of capturing sustainability
  • the development of MCDM methods capable of capturing sustainability and fuzziness (uncertainty, imprecision and inaccurate definition) of the decision problem
  • tools for multicriteria decisions

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Published Papers (5 papers)

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Research

20 pages, 1111 KiB  
Article
Exploring the Barriers to the Advancement of 3D Printing Technology
by Peace Y. L. Liu, James J. H. Liou and Sun-Weng Huang
Mathematics 2023, 11(14), 3068; https://doi.org/10.3390/math11143068 - 11 Jul 2023
Cited by 5 | Viewed by 2367
Abstract
3D printing technology is suitable for application in advancing digitization in dentistry. However, the use of this technology in the dental field is not as widespread as expected. The study discusses the barriers to advancing 3D printing technology in dentistry. First, Fuzzy Delphi [...] Read more.
3D printing technology is suitable for application in advancing digitization in dentistry. However, the use of this technology in the dental field is not as widespread as expected. The study discusses the barriers to advancing 3D printing technology in dentistry. First, Fuzzy Delphi was used to conduct in-depth interviews with experts to explore what barriers prevent the advancement of 3D printing technology in dentistry. Second, the decision-making and trial assessment laboratory (DEMATEL) was used to identify the cause-and-effect relationship among barriers. Because DEMATEL relies on the expert decision-making system, experts often have different experiences and backgrounds, so judgment results are often uncertain and inconsistent. Therefore, this study proposes using a rough-Z-number to integrate opinions among experts, which can effectively overcome the problems of inconsistency and uncertainty. After analyzing the results, we found that “lack of standard infrastructure” is the most important barrier to the advancement of 3D printing in dentistry, and this study provides improvement strategies based on the results. The results put forward countermeasures for the barriers to the promotion of 3D printing technology in dentistry, which will make the development of dental digitization more effective. Full article
(This article belongs to the Special Issue Multiple Criteria Decision Making, 2nd Edition)
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39 pages, 8890 KiB  
Article
Combined Framework of Multicriteria Methods to Identify Quality Attributes in Augmented Reality Applications
by Luz E. Gutiérrez, José Javier Samper, Daladier Jabba, Wilson Nieto, Carlos A. Guerrero, Mark M. Betts and Héctor A. López-Ospina
Mathematics 2023, 11(13), 2834; https://doi.org/10.3390/math11132834 - 24 Jun 2023
Cited by 1 | Viewed by 1743
Abstract
This study proposes a combined framework of multicriteria decision methods to describe, prioritize, and group the quality attributes related to the user experience of augmented reality applications. The attributes were identified based on studies of high-impact repositories. A hierarchy of the identified attributes [...] Read more.
This study proposes a combined framework of multicriteria decision methods to describe, prioritize, and group the quality attributes related to the user experience of augmented reality applications. The attributes were identified based on studies of high-impact repositories. A hierarchy of the identified attributes was built through the multicriteria decision methods Fuzzy Cognitive Maps and DEMATEL. Additionally, a statistical analysis of clusters was developed to determine the most relevant attributes and apply these results in academic and industrial contexts. The main contribution of this study was the categorization of user-experience quality attributes in augmented reality applications, as well as the grouping proposal. Usability, Satisfaction, Stimulation, Engagement, and Aesthetics were found to be among the most relevant attributes. After carrying out the multivariate analysis, two clusters were found with the largest grouping of attributes, oriented to security, representation, social interaction, aesthetics, ergonomics of the application, and its relationship with the user’s emotions. In conclusion, the combination of the three methods helped to identify the importance of the attributes in training processes. The holistic and detailed vision of the causal, impact, and similarity relationships between the 87 attributes analyzed were also considered. This framework will allow the generation of a baseline for the use of multicriteria methods in research into relevant aspects of Augmented Reality. Full article
(This article belongs to the Special Issue Multiple Criteria Decision Making, 2nd Edition)
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18 pages, 1480 KiB  
Article
Evaluating Natural Hazards in Cities Using a Novel Integrated MCDM Approach (Case Study: Tehran City)
by Mahdi Bitarafan, Kambod Amini Hosseini and Sarfaraz Hashemkhani Zolfani
Mathematics 2023, 11(8), 1936; https://doi.org/10.3390/math11081936 - 20 Apr 2023
Cited by 5 | Viewed by 1627
Abstract
Tehran, the capital of Iran, is the largest and most populous city in Iran, which is of great importance due to its large population and abundant infrastructure. One of the most critical issues in this city is its need for resilience against all [...] Read more.
Tehran, the capital of Iran, is the largest and most populous city in Iran, which is of great importance due to its large population and abundant infrastructure. One of the most critical issues in this city is its need for resilience against all kinds of threats, including natural hazards, because its development was not based on territorial geography. In other words, in developing this 700 square kilometer area, attention has yet to be paid to its different zones. Different zones include the mountains, Shemiranat’s alluvial cone area, the Tehran plain, etc. Main and minor faults, surface and underground water resources of the land, differences in formations between various parts of the land, the microclimate of the land in its multiple aspects, local and synoptic air currents, etc., have not been influential in urban development. The most crucial goal of this study is to identify and screen natural hazards in Tehran to improve this city’s resilience by introducing a novel integrated MCDM method based on ANP and The Combined Compromise Solution method with Maximum Variance (MV-CoCoSo). Therefore, to increase the strength of Tehran against these disasters, the natural hazards of Tehran must first be identified and ranked. In this regard, practical criteria for evaluating Tehran’s resilience were identified using library resources and the formation of expert groups. Then, using the ANP method, the comparative weightings of these effective criteria was investigated. Based on the results obtained, the disaster consequence criterion had the highest importance with a weight of 0.4361, followed by the disaster severity scale criterion with a weight of 0.2371, and the secondary threat possibility criterion (with a weight of 0.1232) was ranked third. Finally, using the MV-CoCoSo method, the natural hazards of Tehran city were classified based on the evaluated criteria. Tehran City’s three significant disasters were earthquakes, floods, and landslides. In addition, two experiments were designed to assess the robustness of the research methodology. Full article
(This article belongs to the Special Issue Multiple Criteria Decision Making, 2nd Edition)
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18 pages, 967 KiB  
Article
Machine Learning-Driven Approach for Large Scale Decision Making with the Analytic Hierarchy Process
by Marcos Antonio Alves, Ivan Reinaldo Meneghini, António Gaspar-Cunha and Frederico Gadelha Guimarães
Mathematics 2023, 11(3), 627; https://doi.org/10.3390/math11030627 - 26 Jan 2023
Cited by 2 | Viewed by 3436
Abstract
The Analytic Hierarchy Process (AHP) multicriteria method can be cognitively demanding for large-scale decision problems due to the requirement for the decision maker to make pairwise evaluations of all alternatives. To address this issue, this paper presents an interactive method that uses online [...] Read more.
The Analytic Hierarchy Process (AHP) multicriteria method can be cognitively demanding for large-scale decision problems due to the requirement for the decision maker to make pairwise evaluations of all alternatives. To address this issue, this paper presents an interactive method that uses online learning to provide scalability for AHP. The proposed method involves a machine learning algorithm that learns the decision maker’s preferences through evaluations of small subsets of solutions, and guides the search for the optimal solution. The methodology was tested on four optimization problems with different surfaces to validate the results. We conducted a one factor at a time experimentation of each hyperparameter implemented, such as the number of alternatives to query the decision maker, the learner method, and the strategies for solution selection and recommendation. The results demonstrate that the model is able to learn the utility function that characterizes the decision maker in approximately 15 iterations with only a few comparisons, resulting in significant time and cognitive effort savings. The initial subset of solutions can be chosen randomly or from a cluster. The subsequent ones are recommended during the iterative process, with the best selection strategy depending on the problem type. Recommendation based solely on the smallest Euclidean or Cosine distances reveals better results on linear problems. The proposed methodology can also easily incorporate new parameters and multicriteria methods based on pairwise comparisons. Full article
(This article belongs to the Special Issue Multiple Criteria Decision Making, 2nd Edition)
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17 pages, 1206 KiB  
Article
Key Success Factors of Sustainable Organization for Traditional Manufacturing Industries: A Case Study in Taiwan
by Shih-Hsien Tseng, Hsiu-Chuan Chen and Tien Son Nguyen
Mathematics 2022, 10(22), 4389; https://doi.org/10.3390/math10224389 - 21 Nov 2022
Cited by 3 | Viewed by 2081
Abstract
Even sustainable organizations have received overwhelming attention, but there is a lack of studies to explore the key success factors for sustainable traditional manufacturing based on expert opinions. The purpose of this study was to explore the key success factors for sustainable development [...] Read more.
Even sustainable organizations have received overwhelming attention, but there is a lack of studies to explore the key success factors for sustainable traditional manufacturing based on expert opinions. The purpose of this study was to explore the key success factors for sustainable development in traditional industries through expert knowledge. In this study, the Delphi method was applied to construct the research framework with the most appropriate criteria. Moreover, we proposed an effective solution based on the Decision-Making Trial and Evaluation Laboratory (DEMATEL)-based Analytic Network Process (ANP) to determine the correlation and causality of these factors based on the decision laboratory method for multi-criteria decision-making. We also integrated the importance–performance analysis to illustrate the attributes improvement priorities. Our results show that managers and policy-makers should concentrate more on knowledge management to enhance the sustainability of organizations. Moreover, managers should keep teamwork and employee engagement at a high level to achieve the goal of organizations. Additionally, the theoretical and practical implications provide five priority indicators for the success of a sustainable organization. Full article
(This article belongs to the Special Issue Multiple Criteria Decision Making, 2nd Edition)
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