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Symmetry
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Advances in Fuzzy Sets with Their Applications in Complex and...
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Advances in Fuzzy Sets with Their Applications in Complex and Symmetry Multiple Criteria Decision-Making

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

Deadline for manuscript submissions: closed (30 April 2022) | Viewed by 3290

Special Issue Editors

Dr. Jun Wang

E-Mail Website
Guest Editor
School of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, China
Interests: fuzzy sets theory; multiple criteria decision-making; aggregation operators; large scale group decision-making
Dr. Yuping Xing

E-Mail Website
Guest Editor
Glorious Sun School of Business and Management, Donghua University, Shanghai 200051, China
Interests: fuzzy group decision making; intelligent computing; health-care management
Dr. Donghua Chen

E-Mail Website
Guest Editor
School of Information Technology and Management, University of International Business and Economics, Beijing 100029, China
Interests: fuzzy logic; natural language processing; multimodal machine learning; meta-learning; and distributed computing

Special Issue Information

Dear Colleagues,

Multiple criteria decision-making (MCDM) refers to a kind of decision-making problem in which possible alternatives are evaluated by decision makers under a collection of criteria. MCDM is very common in economics, management, and even daily life. Hence, MCDM theories and methods have received a great deal of attention in academic sectors. In practice, as most MCDM problems are very complex, it is difficult for decision makers to use crisp numbers to express their evaluation information over alternatives. In addition, MCDM problems in real life are characterized by symmetry, asymmetry, and complexity. It was Prof. Zadeh who initiated the concept of fuzzy sets, which employ the so-called “membership function” to describe the degree to which an element belongs to a given fixed set. A fuzzy set is a powerful tool to handle uncertainty and ambiguity, and generally the notions of symmetry and asymmetry are also exhibited in fuzzy set theory. With the aid of fuzzy set theory, it has become much easier for decision makers to provide their preference information in the MCDM process. Based on Zadeh’s pioneering works, quite a few extensions of the classical fuzzy set theory have been proposed, such as intuitionistic fuzzy sets, hesitant fuzzy sets, dual hesitant fuzzy sets, Pythagorean fuzzy sets, q-rung orthopair fuzzy sets, probabilistic linguistic term sets, and probabilistic hesitant fuzzy sets. These theories provide decision makers useful and sufficient manners to appropriately express their cognition over alternatives in the process of MCDM. In addition, based on these theories, many powerful MCDM methods have been proposed and they have also been widely applied in solving realistic decision-making problems. Since real-world MCDM problems are becoming increasingly complex, novel fuzzy set theories and corresponding MCDM methods are of high necessity.

This Special Issue aims to emphasize the advances and developments in fuzzy set theory and their applications in MCDM, which would be of great significance to expand new theoretical directions and practical applications. We invite researchers and experts worldwide to submit high-quality original research papers that focus on recent advances in fuzzy-sets-based concepts and methodologies, and their applications in MCDM. This Special Issue will be focused on research topics including but not limited to the following:

  • Novel fuzzy representation models;
  • Intuitionistic fuzzy sets;
  • Pythagorean fuzzy sets;
  • Q-rung orthopair fuzzy sets;
  • Dual hesitant fuzzy sets;
  • Probabilistic hesitant fuzzy sets;
  • Probabilistic linguistic term sets;
  • Fuzzy entropy;
  • Fuzzy soft sets;
  • Fuzzy information fusion and aggregation operators;
  • Multiple criteria decision-making methods;
  • Any application areas with fuzzy-sets-based uncertainty modelling;
  • Applications based on fuzzy set theory based in health-care management

Dr. Jun Wang
Dr. Yuping Xing
Dr. Donghua Chen
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

  • Novel fuzzy representation models
  • Intuitionistic fuzzy sets
  • Pythagorean fuzzy sets
  • Q-rung orthopair fuzzy sets
  • Dual hesitant fuzzy sets
  • Probabilistic hesitant fuzzy sets
  • Probabilistic linguistic term sets
  • Fuzzy entropy
  • Fuzzy soft sets
  • Fuzzy information fusion and aggregation operators
  • Multiple criteria decision-making methods
  • Any application areas with fuzzy-sets-based uncertainty modelling
  • Applications based on fuzzy set theory based in health-care management

Published Papers (2 papers)

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Research

30 pages, 2878 KiB  
Article
Bi-Matrix Games with General Intuitionistic Fuzzy Payoffs and Application in Corporate Environmental Behavior
by Shuying Li and Guoping Tu
Symmetry 2022, 14(4), 671; https://0-doi-org.brum.beds.ac.uk/10.3390/sym14040671 - 24 Mar 2022
Cited by 6 | Viewed by 1409
Abstract
Uncertainty is common in miscellaneous decision-making problems, including bi-matrix games. The uncertainty of bi-matrix games is caused by the complexity of the game environment and the limitations of players’ cognition rather than the asymmetry of information. Therefore, it is hard for players to [...] Read more.
Uncertainty is common in miscellaneous decision-making problems, including bi-matrix games. The uncertainty of bi-matrix games is caused by the complexity of the game environment and the limitations of players’ cognition rather than the asymmetry of information. Therefore, it is hard for players to precisely give their crisp payoff values. In this paper, a new method considering the acceptance degree that the general intuitionistic fuzzy constraints may be violated is developed to solve general intuitionistic fuzzy bi-matrix games (GIFBMGs). In the method, a new asymmetric general intuitionistic fuzzy number (GIFN) and its cut sets are firstly defined. Then, the order relationship of GIFNs and the definitions of α and β-bi-matrix games are proposed. Afterwards, the constructed general intuitionistic fuzzy quadratic program is converted into an interval bi-objective program on the basis of the order relationship of GIFNs. Furthermore, the interval bi-objective program is converted into a multi-objective quadratic program based on the combination of interval order relationship and the player’s acceptance degree. A goal programming approach is put forward to solve the multi-objective quadratic program. Finally, the validity of the proposed method is verified with a numerical example for corporate environmental behavior (CEB), and some comparative analyses are conducted to show the superiority of the proposed method. Full article
(This article belongs to the Special Issue Advances in Fuzzy Sets with Their Applications in Complex and Symmetry Multiple Criteria Decision-Making)
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25 pages, 10307 KiB  
Article
A Novel Decision-Making Method for Selecting Superintendent Based on a Q-Rung Dual Hesitant Fuzzy Power Partitioned Bonferroni Mean Operator
by Tiedong Chen and Long Ye
Symmetry 2022, 14(3), 590; https://0-doi-org.brum.beds.ac.uk/10.3390/sym14030590 - 16 Mar 2022
Cited by 3 | Viewed by 1236
Abstract
The Q-rung dual hesitant fuzzy (q-RDHF) set is famous for expressing information composed of asymmetry evaluations, because it allows for several possible evaluations in both the membership degree and non-membership degree. Compared with some existing extended fuzzy theories, the q-RDHF set is more [...] Read more.
The Q-rung dual hesitant fuzzy (q-RDHF) set is famous for expressing information composed of asymmetry evaluations, because it allows for several possible evaluations in both the membership degree and non-membership degree. Compared with some existing extended fuzzy theories, the q-RDHF set is more superior and flexible because it can handle asymmetric assessments. In order to assemble the evaluation information expressed by q-RDHF elements, this paper aims to propose new operators to integrate q-RDHF elements. The partitioned Bonferroni mean (PBM) operator is well-known for its advantages in coping with the inhomogeneous relationship between asymmetry input arguments. In this paper, we combine the PBM operator with the power average operator, and propose a family of q-RDHF power PBM operators. Some theorems and special cases for the new proposed operators are discussed. Furthermore, we provide a general framework for dealing with multiple attribute decision-making (MADM) problems using the novel proposed method. To better show the calculation details, a numerical case study of the application of the proposed method in a superintendent selection problem is introduced. In addition, we utilize the proposed method to compare it with some existing methods in order to show its flexibility and superiority. The results show that our method is much more advantageous when considering flexible actual situations. Finally, the conclusion is given. The main contributions of this study are to propose an appropriate method to solve unbalanced and asymmetry information in a q-RDHF environment, and to apply it into a realistic superintendent selection problem. Full article
(This article belongs to the Special Issue Advances in Fuzzy Sets with Their Applications in Complex and Symmetry Multiple Criteria Decision-Making)
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