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Symmetry
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Symmetric and Asymmetric Data in Solution Models, Part II
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Symmetric and Asymmetric Data in Solution Models, Part II

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".

Deadline for manuscript submissions: 31 March 2025 | Viewed by 26300

Special Issue Editors

Prof. Dr. Edmundas Kazimieras Zavadskas

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Guest Editor
Research Institute of Sustainable Construction, Vilnius Gediminas Technical University, LT-10223 Vilnius, Lithuania
Interests: operations research; optimization and decision analysis; multicriteria decision making; multiattribute decision making (MADM); decision support systems; civil engineering; energy; sustainable development; fuzzy sets theory; fuzzy multicriteria decision making; sustainability; management; game theory and economical computing knowledge management
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Jurgita Antuchevičienė

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Guest Editor
Department of Construction Management and Real Estate, Vilnius Gediminas Technical University, LT-10223 Vilnius, Lithuania
Interests: multi-criteria decision-making (MCDM); multiattribute decision making (MADM); operations research; decision support systems; multiple-criteria optimization in construction technology and management; decision making under uncertainty; fuzzy sets theory; civil engineering; sustainable development; sustainable construction; investments; knowledge management
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Zenonas Turskis

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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,

This Special Issue intends to cover symmetric and asymmetric data occurring in real-life problems. Symmetry and structural regularity are essential concepts in many natural and human-made objects and play a crucial role in problem solutions. While the complexity and risks inherent in problem-solution models, along with different indicators of success and failure, may contribute to the difficulties in their performance evaluation, multiple solutions generally exist. Asymmetry of information and goals occurs in sustainable problem-solving processes. The existence of data asymmetry in economics and business issues causes difficulties when achieving an optimal solution. Symmetric and asymmetric information properties are essential for extreme situations and for public, environmental, and occupational health problem modelling. Therefore, authors can propose various solution models as an integrated tool to find a balance between sustainable global development components, i.e., to find symmetry concerning goals, risks, and constraints, to cope with complicated problems. We invite authors to submit their theoretical or experimental research presenting engineering and other problem-solving models dealing with the symmetry and asymmetry of different data types.

Prof. Dr. Edmundas Kazimieras Zavadskas
Prof. Dr. Jurgita Antuchevičienė
Prof. Dr. Zenonas Turskis
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 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

  • Symmetry and asymmetry particularities in sustainable development modelling
  • Symmetry and asymmetry particularities in economics and business modelling
  • Symmetry and asymmetry particularities in public, environmental, and occupational health
  • Symmetry and asymmetry particularities in engineering and technology
  • Symmetric and asymmetric information properties for extreme situation modelling
  • Data mining and integration of symmetric and asymmetric information
  • Description of symmetric and asymmetric data in models
  • Multiple-criteria problem solution models with certainly and vague determined data
  • Symmetric and asymmetric risks of problems
  • Hybrid problem solution models
  • Fuzzy sets
  • Intuitionistic fuzzy sets
  • Neutrosophic sets
  • Rough sets
  • Grey systems
  • Novel descriptions of sets
  • Computer-aided problem solution

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Published Papers (6 papers)

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Research

18 pages, 931 KiB  
Article
Comparison of Selected Numerical Methods for Solving Integro-Differential Equations with the Cauchy Kernel
by Rafał Brociek and Mariusz Pleszczyński
Symmetry 2024, 16(2), 233; https://doi.org/10.3390/sym16020233 - 14 Feb 2024
Cited by 2 | Viewed by 1213
Abstract
The integro-differential equation with the Cauchy kernel is used in many different technical problems, such as in circuit analysis or gas infrared radiation studies. Therefore, it is important to be able to solve this type of equation, even in an approximate way. This [...] Read more.
The integro-differential equation with the Cauchy kernel is used in many different technical problems, such as in circuit analysis or gas infrared radiation studies. Therefore, it is important to be able to solve this type of equation, even in an approximate way. This article compares two approaches for solving this type of equation. One of the considered methods is based on the application of the differential Taylor series, while the second approach uses selected heuristic algorithms inspired by the behavior of animals. Due to the problem domain, which is symmetric, and taking into account the form of the function appearing in this equation, we can use this symmetry in some cases. The paper also presents numerical examples illustrating how each method works and comparing the discussed approaches. Full article
(This article belongs to the Special Issue Symmetric and Asymmetric Data in Solution Models, Part II)
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18 pages, 1956 KiB  
Article
Modifying Hellwig’s Method for Multi-Criteria Decision-Making with Mahalanobis Distance for Addressing Asymmetrical Relationships
by Ewa Roszkowska
Symmetry 2024, 16(1), 77; https://doi.org/10.3390/sym16010077 - 6 Jan 2024
Cited by 3 | Viewed by 1601
Abstract
Hellwig’s method is a multi-criteria decision-making technique designed to facilitate the ranking of alternatives based on their proximity to the ideal solution. Typically, this approach calculates distances using the Euclidean norm, assuming implicitly that the considered criteria are independent. However, in real-world situations, [...] Read more.
Hellwig’s method is a multi-criteria decision-making technique designed to facilitate the ranking of alternatives based on their proximity to the ideal solution. Typically, this approach calculates distances using the Euclidean norm, assuming implicitly that the considered criteria are independent. However, in real-world situations, the assumption of criteria independence is rarely met. The paper aims to propose an extension of Hellwig’s method by incorporating the Mahalanobis distance. Substituting the Euclidean distance with the Mahalanobis distance has proven to be effective in handling correlations among criteria, especially in the context of asymmetrical relationships between criteria. Subsequently, we investigate the impact of the Euclidean and Mahalanobis distance measures on the several variants of Hellwig procedures, analyzing examples based on various illustrative data with 10 alternatives and 4 criteria. Additionally, we examine the influence of three normalization formulas in Hellwig’s aggregation procedures. The investigation results indicate that both the distance measure and normalization formulas have some impact on the final rankings. The evaluation and ranking of alternatives using the Euclidean distance measure are influenced by the normalization formula, albeit to a limited extent. In contrast, the Mahalanobis distance-based Hellwig’s method remains unaffected by the choice of normalization formulas. The study concludes that the ranking of alternatives is strongly dependent on the distance measure employed, whether it is Euclidean or Mahalanobis. The Mahalanobis distance-based Hellwig method is deemed a valuable tool for decision-makers in real-life situations. It enables the evaluation of alternatives by considering interactions between criteria, providing a more comprehensive perspective for decision-making. Full article
(This article belongs to the Special Issue Symmetric and Asymmetric Data in Solution Models, Part II)
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17 pages, 1296 KiB  
Article
A Proposed DEA Window Analysis for Assessing Efficiency from Asymmetry Dynamic Data
by Abbas Al-Refaie and Natalija Lepkova
Symmetry 2023, 15(9), 1650; https://doi.org/10.3390/sym15091650 - 26 Aug 2023
Viewed by 1212
Abstract
Nowadays, one of the main challenges facing production management is how to enhance the performance of manufacturing processes by utilizing asymmetry input and output data. This research, therefore, developed a framework for window analysis in data envelopment analysis (DEA) for evaluating the overall [...] Read more.
Nowadays, one of the main challenges facing production management is how to enhance the performance of manufacturing processes by utilizing asymmetry input and output data. This research, therefore, developed a framework for window analysis in data envelopment analysis (DEA) for evaluating the overall technical efficiencies from asymmetry dynamic input and output data. The framework was applied to assess the technical (TE), managerial (PTE), and scale (SE) efficiencies of a blowing machine under three fuzzy input variables (planned production quantity, number of defectives, and idle time) and a fuzzy output variable (actual or target production quantity). The efficiency measures were then evaluated for all DMUs at low (L), middle (M), and high (H) data levels. The obtained optimal fuzzy efficiencies were then transformed into a single crisp optimal efficiency. The results showed that all seven DMUs of the blowing machine were technically inefficient. The input and output slacks were estimated and utilized to determine the necessary improvement actions. Improvement results revealed that the optimal TE, PTE, and SE were significantly improved, which may result in significant savings in production and quality costs. In conclusion, the proposed framework is effective in improving the efficiency of the blowing process and can be utilized for efficiency assessment in a wide range of applications. Full article
(This article belongs to the Special Issue Symmetric and Asymmetric Data in Solution Models, Part II)
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31 pages, 1226 KiB  
Article
Modeling the Covariance of Financial Assets Using Neutrosophic Fuzzy Numbers
by Marcel-Ioan Boloș, Ioana-Alexandra Bradea and Camelia Delcea
Symmetry 2023, 15(2), 320; https://doi.org/10.3390/sym15020320 - 23 Jan 2023
Cited by 2 | Viewed by 1670
Abstract
This paper aims to model the covariance of financial assets using neutrosophic fuzzy numbers. Two main concepts are discussed and used, namely the neutrosophic covariance of the financial assets and the independent neutrosophic portfolios. In terms of methodology, a three-step approach is proposed [...] Read more.
This paper aims to model the covariance of financial assets using neutrosophic fuzzy numbers. Two main concepts are discussed and used, namely the neutrosophic covariance of the financial assets and the independent neutrosophic portfolios. In terms of methodology, a three-step approach is proposed with the purpose of identifying the independent neutrosophic portfolio return, the independent neutrosophic portfolio risk and the structure of the independent neutrosophic portfolio. For this purpose, neutrosophic fuzzy theory is chosen for this type of approach as it allows a proper modeling of the financial performance indicators by taking into account the probabilities of their achievement. This action is possible even in the situation in which linguistic variables are used for better characterizing the values of the recorded data. Numerical examples are provided in each stage of the methodology description for a better understanding of the proposed approach. The results of the study can be used to substantiate the decisions made by the capital market investors. Full article
(This article belongs to the Special Issue Symmetric and Asymmetric Data in Solution Models, Part II)
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17 pages, 308 KiB  
Article
Information Reliability Assessment and Filtering for Decision Making. Case Study of Lithuanian and China Students’ Life Goals Survey Data
by Aleksandras Krylovas, Natalja Kosareva and Stanislav Dadelo
Symmetry 2021, 13(12), 2452; https://doi.org/10.3390/sym13122452 - 20 Dec 2021
Viewed by 2246
Abstract
This article presents the methodology and tools to evaluate the reliability of quantitative sociological research data. The problem of filtering unreliable data is usually solved by statistical methods. This article proposes an improved method for filtering unreliable data. In this case, the statistical [...] Read more.
This article presents the methodology and tools to evaluate the reliability of quantitative sociological research data. The problem of filtering unreliable data is usually solved by statistical methods. This article proposes an improved method for filtering unreliable data. In this case, the statistical methods are not applied to the initial data but the value of the distance function between the two preferences. This allows for the disclosure of conflicting or erroneous data. Calculation of the distance between two preferences and prioritisation of life goals are based on binary relation theory, where the properties of symmetry (antisymmetry) are very important. The article presents a case study on 11 life goals evaluation and ranking by Lithuanian and China students. The study revealed that the China student data filtered at least twice as much as the Lithuanian student data, i.e., they are less reliable. The filtered data show that students of both countries ranked the most and the least important life goals in a very similar way with minimum deviations detected in the ranking results. Full article
(This article belongs to the Special Issue Symmetric and Asymmetric Data in Solution Models, Part II)
20 pages, 7946 KiB  
Article
Determination of Objective Weights Using a New Method Based on the Removal Effects of Criteria (MEREC)
by Mehdi Keshavarz-Ghorabaee, Maghsoud Amiri, Edmundas Kazimieras Zavadskas, Zenonas Turskis and Jurgita Antucheviciene
Symmetry 2021, 13(4), 525; https://doi.org/10.3390/sym13040525 - 24 Mar 2021
Cited by 344 | Viewed by 16494
Abstract
The weights of criteria in multi-criteria decision-making (MCDM) problems are essential elements that can significantly affect the results. Accordingly, researchers developed and presented several methods to determine criteria weights. Weighting methods could be objective, subjective, and integrated. This study introduces a new method, [...] Read more.
The weights of criteria in multi-criteria decision-making (MCDM) problems are essential elements that can significantly affect the results. Accordingly, researchers developed and presented several methods to determine criteria weights. Weighting methods could be objective, subjective, and integrated. This study introduces a new method, called MEREC (MEthod based on the Removal Effects of Criteria), to determine criteria’ objective weights. This method uses a novel idea for weighting criteria. After systematically introducing the method, we present some computational analyses to confirm the efficiency of the MEREC. Firstly, an illustrative example demonstrates the procedure of the MEREC for calculation of the weights of criteria. Secondly, a comparative analysis is presented through an example for validation of the introduced method’s results. Additionally, we perform a simulation-based analysis to verify the reliability of MEREC and the stability of its results. The data of the MCDM problems generated for making this analysis follow a prevalent symmetric distribution (normal distribution). We compare the results of the MEREC with some other objective weighting methods in this analysis, and the analysis of means (ANOM) for variances shows the stability of its results. The conducted analyses demonstrate that the MEREC is efficient to determine objective weights of criteria. Full article
(This article belongs to the Special Issue Symmetric and Asymmetric Data in Solution Models, Part II)
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