Special Issue "Fuzzy Techniques for Decision Making 2018"

A special issue of Symmetry (ISSN 2073-8994).

Deadline for manuscript submissions: 30 November 2018

Special Issue Editor

Guest Editor
Prof. Dr. José Carlos R. Alcantud

Department of Economics and Economic History, University of Salamanca, Spain
Website | E-Mail
Phone: +34-923-294666
Fax: +34-923-294500 (ext 4666)
Interests: decision theory; social choice; mathematical economics;fuzzy set theory

Special Issue Information

Dear Colleagues,

Zadeh's fuzzy set theory incorporates impreciseness of data and evaluations by imputing the degrees to which objects belong to a set. Its appearance induced the rise of several related theories, which codify subjectivity, uncertainty, imprecision, or roughness of evaluations. Their rationale is to produce new and more flexible methodologies in order to realistically model a variety of concrete decision problems. This Special Issue invites contributions addressing novel tools, techniques and methodologies for decision making (e.g., group or multi-criteria decision making) in the context of these theories. Therefore we intend to garner articles in a variety of setups including fuzzy sets, fuzzy soft sets, type-2 fuzzy sets, interval-valued fuzzy sets, hesitant fuzzy sets, fuzzy rough sets and rough fuzzy sets. Extensive review papers which refer to the latest research findings, as well as application papers, are welcome.

Prof. Dr. José Carlos R. Alcantud
Guest Editor

Manuscript Submission Information

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Keywords

  • Fuzzy set
  • Fuzzy soft set
  • Type-2 fuzzy set
  • Interval-valued fuzzy set
  • Hesitant fuzzy set
  • Neutrosophic set
  • Aggregation operator
  • Similarity and distance measure
  • Group decision making
  • Multi-criteria decision making
  • Symmetrical decision model

Published Papers (11 papers)

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Research

Open AccessArticle A Three-Dimensional Constrained Ordered Weighted Averaging Aggregation Problem with Lower Bounded Variables
Symmetry 2018, 10(8), 339; https://doi.org/10.3390/sym10080339
Received: 25 July 2018 / Revised: 9 August 2018 / Accepted: 9 August 2018 / Published: 13 August 2018
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Abstract
We consider the constrained ordered weighted averaging (OWA) aggregation problem with a single constraint and lower bounded variables. For the three-dimensional constrained OWA aggregation problem with lower bounded variables, we present four types of solution depending on the number of zero elements. According
[...] Read more.
We consider the constrained ordered weighted averaging (OWA) aggregation problem with a single constraint and lower bounded variables. For the three-dimensional constrained OWA aggregation problem with lower bounded variables, we present four types of solution depending on the number of zero elements. According to the computerized experiment we perform, the lower bounds can affect the solution types, thereby affecting the optimal solution of the three-dimensional constrained OWA aggregation problem with lower bounded variables. Full article
(This article belongs to the Special Issue Fuzzy Techniques for Decision Making 2018)
Open AccessArticle A Multi-Level Privacy-Preserving Approach to Hierarchical Data Based on Fuzzy Set Theory
Symmetry 2018, 10(8), 333; https://doi.org/10.3390/sym10080333
Received: 28 July 2018 / Revised: 8 August 2018 / Accepted: 9 August 2018 / Published: 10 August 2018
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Abstract
Nowadays, more and more applications are dependent on storage and management of semi-structured information. For scientific research and knowledge-based decision-making, such data often needs to be published, e.g., medical data is released to implement a computer-assisted clinical decision support system. Since this data
[...] Read more.
Nowadays, more and more applications are dependent on storage and management of semi-structured information. For scientific research and knowledge-based decision-making, such data often needs to be published, e.g., medical data is released to implement a computer-assisted clinical decision support system. Since this data contains individuals’ privacy, they must be appropriately anonymized before to be released. However, the existing anonymization method based on l-diversity for hierarchical data may cause serious similarity attacks, and cannot protect data privacy very well. In this paper, we utilize fuzzy sets to divide levels for sensitive numerical and categorical attribute values uniformly (a categorical attribute value can be converted into a numerical attribute value according to its frequency of occurrences), and then transform the value levels to sensitivity levels. The privacy model ( α l e v h , k)-anonymity for hierarchical data with multi-level sensitivity is proposed. Furthermore, we design a privacy-preserving approach to achieve this privacy model. Experiment results demonstrate that our approach is obviously superior to existing anonymous approach in hierarchical data in terms of utility and security. Full article
(This article belongs to the Special Issue Fuzzy Techniques for Decision Making 2018)
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Open AccessArticle Multiple-Attribute Decision-Making Method Using Similarity Measures of Hesitant Linguistic Neutrosophic Numbers Regarding Least Common Multiple Cardinality
Symmetry 2018, 10(8), 330; https://doi.org/10.3390/sym10080330
Received: 10 July 2018 / Revised: 5 August 2018 / Accepted: 7 August 2018 / Published: 9 August 2018
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Abstract
Linguistic neutrosophic numbers (LNNs) are a powerful tool for describing fuzzy information with three independent linguistic variables (LVs), which express the degrees of truth, uncertainty, and falsity, respectively. However, existing LNNs cannot depict the hesitancy of the decision-maker (DM). To solve this issue,
[...] Read more.
Linguistic neutrosophic numbers (LNNs) are a powerful tool for describing fuzzy information with three independent linguistic variables (LVs), which express the degrees of truth, uncertainty, and falsity, respectively. However, existing LNNs cannot depict the hesitancy of the decision-maker (DM). To solve this issue, this paper first defines a hesitant linguistic neutrosophic number (HLNN), which consists of a few LNNs regarding an evaluated object due to DMs’ hesitancy to represent their hesitant and uncertain information in the decision-making process. Then, based on the least common multiple cardinality (LCMC), we present generalized distance and similarity measures of HLNNs, and then develop a similarity measure-based multiple-attribute decision-making (MADM) method to handle the MADM problem in the HLNN setting. Finally, the feasibility of the proposed approach is verified by an investment decision case. Full article
(This article belongs to the Special Issue Fuzzy Techniques for Decision Making 2018)
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Open AccessArticle Picture Hesitant Fuzzy Set and Its Application to Multiple Criteria Decision-Making
Symmetry 2018, 10(7), 295; https://doi.org/10.3390/sym10070295
Received: 21 June 2018 / Revised: 17 July 2018 / Accepted: 18 July 2018 / Published: 20 July 2018
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Abstract
To address the complex multiple criteria decision-making (MCDM) problems in practice, this article proposes the picture hesitant fuzzy set (PHFS) theory based on the picture fuzzy set and the hesitant fuzzy set. First, the concept of PHFS is put forward, and its operations
[...] Read more.
To address the complex multiple criteria decision-making (MCDM) problems in practice, this article proposes the picture hesitant fuzzy set (PHFS) theory based on the picture fuzzy set and the hesitant fuzzy set. First, the concept of PHFS is put forward, and its operations are presented, simultaneously. Second, the generalized picture hesitant fuzzy weighted aggregation operators are developed, and some theorems and reduced operators of them are discussed. Third, the generalized picture hesitant fuzzy prioritized weighted aggregation operators are put forward to solve the MCDM problems that the related criteria are at different priorities. Fourth, two novel MCDM methods combined with the proposed operators are constructed to determine the best alternative in real life. Finally, two numerical examples and an application of web service selection are investigated to illustrate the effectiveness of the proposed methods. The sensitivity analysis shows that the different values of the parameter λ affect the ranking of alternatives, and the proposed operators are compared with several existing MCDM methods to illustrate their advantages. Full article
(This article belongs to the Special Issue Fuzzy Techniques for Decision Making 2018)
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Open AccessArticle Selecting the Optimal Mine Ventilation System via a Decision Making Framework under Hesitant Linguistic Environment
Symmetry 2018, 10(7), 283; https://doi.org/10.3390/sym10070283
Received: 15 June 2018 / Revised: 10 July 2018 / Accepted: 10 July 2018 / Published: 13 July 2018
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Abstract
Ventilation systems are amongst the most essential components of a mine. As the indicators of ventilation systems are in general of ambiguity or uncertainty, the selection of ventilation systems can therefore be regarded as a complex fuzzy decision making problem. In order to
[...] Read more.
Ventilation systems are amongst the most essential components of a mine. As the indicators of ventilation systems are in general of ambiguity or uncertainty, the selection of ventilation systems can therefore be regarded as a complex fuzzy decision making problem. In order to solve such problems, a decision making framework based on a new concept, the hesitant linguistic preference relation (HLPR), is constructed. The basic elements in the HLPR are hesitant fuzzy linguistic numbers (HFLNs). At first, new operational laws and aggregation operators of HFLNs are defined to overcome the limitations in existing literature. Subsequently, a novel comparison method based on likelihood is proposed to obtain the order relationship of two HFLNs. Then, a likelihood-based consistency index is introduced to represent the difference between two hesitant linguistic preference relations (HLPRs). It is a new way to express the consistency degree for the reason that the traditional consistency indices are almost exclusively based on distance measures. Meanwhile, a consistency-improving model is suggested to attain acceptable consistent HLPRs. In addition, a method to receive reasonable ranking results from HLPRs with acceptable consistency is presented. At last, this method is used to pick out the best mine ventilation system under uncertain linguistic decision conditions. A comparison and a discussion are conducted to demonstrate the validity of the presented approach. The results show that the proposed method is effective for selecting the optimal mine ventilation system, and provides references for the construction and management of mines. Full article
(This article belongs to the Special Issue Fuzzy Techniques for Decision Making 2018)
Open AccessArticle Intuitionistic Fuzzy Multiple Attribute Decision-Making Model Based on Weighted Induced Distance Measure and Its Application to Investment Selection
Symmetry 2018, 10(7), 261; https://doi.org/10.3390/sym10070261
Received: 11 June 2018 / Revised: 28 June 2018 / Accepted: 2 July 2018 / Published: 4 July 2018
Cited by 1 | PDF Full-text (262 KB) | HTML Full-text | XML Full-text
Abstract
This paper investigates an intuitionistic fuzzy multiple attribute decision-making method based on weighted induced distance and its application to investment selection. Specifically, an intuitionistic fuzzy weighted induced ordered weighted averaging operator is proposed to eliminate the drawbacks of existing methods by extending the
[...] Read more.
This paper investigates an intuitionistic fuzzy multiple attribute decision-making method based on weighted induced distance and its application to investment selection. Specifically, an intuitionistic fuzzy weighted induced ordered weighted averaging operator is proposed to eliminate the drawbacks of existing methods by extending the functions of the order-induced variables. The main advantage of the proposed operator is its dual roles of the order-inducing variables that can simultaneously induce arguments and moderate associated weights. A further extension of the proposed operator is its adaptation towards measuring intuitionistic fuzzy information more effectively. In addition, a multiple attribute decision-making model based on the proposed distance operators is proposed. Finally, the practicability and validity of the proposed model are illustrated by using a numerical example related to investment selection. Full article
(This article belongs to the Special Issue Fuzzy Techniques for Decision Making 2018)
Open AccessArticle Complex Fuzzy Geometric Aggregation Operators
Symmetry 2018, 10(7), 251; https://doi.org/10.3390/sym10070251
Received: 15 June 2018 / Revised: 25 June 2018 / Accepted: 28 June 2018 / Published: 2 July 2018
Cited by 1 | PDF Full-text (826 KB) | HTML Full-text | XML Full-text
Abstract
A complex fuzzy set is an extension of the traditional fuzzy set, where traditional [0,1]-valued membership grade is extended to the complex unit disk. The aggregation operator plays an important role in many fields, and this paper presents several complex fuzzy geometric aggregation
[...] Read more.
A complex fuzzy set is an extension of the traditional fuzzy set, where traditional [0,1]-valued membership grade is extended to the complex unit disk. The aggregation operator plays an important role in many fields, and this paper presents several complex fuzzy geometric aggregation operators. We show that these operators possess the properties of rotational invariance and reflectional invariance. These operators are also closed on the upper-right quadrant of the complex unit disk. Based on the relationship between Pythagorean membership grades and complex numbers, these operators can be applied to the Pythagorean fuzzy environment. Full article
(This article belongs to the Special Issue Fuzzy Techniques for Decision Making 2018)
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Open AccessArticle A Hybrid Fuzzy Analytic Network Process (FANP) and Data Envelopment Analysis (DEA) Approach for Supplier Evaluation and Selection in the Rice Supply Chain
Symmetry 2018, 10(6), 221; https://doi.org/10.3390/sym10060221
Received: 18 May 2018 / Revised: 12 June 2018 / Accepted: 12 June 2018 / Published: 14 June 2018
Cited by 1 | PDF Full-text (2025 KB) | HTML Full-text | XML Full-text
Abstract
In the market economy, competition is typically due to the difficulty in selecting the most suitable supplier, one that is capable to help a business to develop a profit to the highest value threshold and capable to meet sustainable development features. In addition,
[...] Read more.
In the market economy, competition is typically due to the difficulty in selecting the most suitable supplier, one that is capable to help a business to develop a profit to the highest value threshold and capable to meet sustainable development features. In addition, this research discusses a wide range of consequences from choosing an effective supplier, including reducing production cost, improving product quality, delivering the product on time, and responding flexibly to customer requirements. Therefore, the activities noted above are able to increase an enterprise’s competitiveness. It can be seen that selecting a supplier is complex in that decision-makers must have an understanding of the qualitative and quantitative features for assessing the symmetrical impact of the criteria to reach the most accurate result. In this research, the multi-criteria group decision-making (MCGDM) approach was proposed to solve supplier selection problems. The authors collected data from 25 potential suppliers, and the four main criteria within contain 15 sub-criteria to define the most effective supplier, which has viewed factors, including financial efficiency guarantee, quality of materials, ability to deliver on time, and the conditioned response to the environment to improve the efficiency of the industry supply chain. Initially, fuzzy analytic network process (ANP) is used to evaluate and rank these criteria, which are able to be utilized to clarify important criteria that directly affect the profitability of the business. Subsequently, data envelopment analysis (DEA) models, including the Charnes Cooper Rhodes model (CCR model), Banker Charnes Cooper model (BCC model), and slacks-based measure model (SBM model), were proposed to rank suppliers. The result of the model has proposed 7/25 suppliers, which have a condition response to the enterprises’ supply requirements. Full article
(This article belongs to the Special Issue Fuzzy Techniques for Decision Making 2018)
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Open AccessFeature PaperArticle Hesitant Fuzzy Linguistic Aggregation Operators Based on the Hamacher t-norm and t-conorm
Symmetry 2018, 10(6), 189; https://doi.org/10.3390/sym10060189
Received: 11 May 2018 / Revised: 26 May 2018 / Accepted: 30 May 2018 / Published: 31 May 2018
Cited by 1 | PDF Full-text (1240 KB) | HTML Full-text | XML Full-text
Abstract
Hesitant fuzzy linguistic (HFL) term set, as a very flexible tool to represent the judgments of decision makers, has attracted the attention of many researchers. In recent years, some HFL aggregation operators have been developed to aggregate the HFL information. However, most of
[...] Read more.
Hesitant fuzzy linguistic (HFL) term set, as a very flexible tool to represent the judgments of decision makers, has attracted the attention of many researchers. In recent years, some HFL aggregation operators have been developed to aggregate the HFL information. However, most of these operators are proposed based on the Algebraic product and Algebraic sum. In this paper, we presented some HFL aggregation operators to handle HFL information based on Hamacher triangle norms. We first define new operational laws on the HFL element according to Hamacher triangle norms. Then we present a family of HFL Hamacher aggregation operators, including the HFL Hamacher weighted averaging, HFL Hamacher weighted geometric, HFL Hamacher power weighted averaging and HFL Hamacher power weighted geometric operators and their generalized forms. We also investigate some special cases and properties of these operators in detail. Furthermore, we develop two approaches based on the proposed operators to deal with the multi-criteria decision-making problem with HFL information. Finally, a numerical example with regard to choosing a suitable city to release sharing car is provided to illustrate the feasibility of the proposed method, and the advantages of the proposed methods are shown by conducting a sensitivity and comparative analysis. Full article
(This article belongs to the Special Issue Fuzzy Techniques for Decision Making 2018)
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Open AccessArticle A Novel Approach to Multi-Attribute Group Decision-Making with q-Rung Picture Linguistic Information
Symmetry 2018, 10(5), 172; https://doi.org/10.3390/sym10050172
Received: 20 April 2018 / Revised: 10 May 2018 / Accepted: 14 May 2018 / Published: 18 May 2018
Cited by 1 | PDF Full-text (1006 KB) | HTML Full-text | XML Full-text
Abstract
The proposed q-rung orthopair fuzzy set (q-ROFS) and picture fuzzy set (PIFS) are two powerful tools for depicting fuzziness and uncertainty. This paper proposes a new tool, called q-rung picture linguistic set (q-RPLS) to deal with vagueness
[...] Read more.
The proposed q-rung orthopair fuzzy set (q-ROFS) and picture fuzzy set (PIFS) are two powerful tools for depicting fuzziness and uncertainty. This paper proposes a new tool, called q-rung picture linguistic set (q-RPLS) to deal with vagueness and impreciseness in multi-attribute group decision-making (MAGDM). The proposed q-RPLS takes full advantages of q-ROFS and PIFS and reflects decision-makers’ quantitative and qualitative assessments. To effectively aggregate q-rung picture linguistic information, we extend the classic Heronian mean (HM) to q-RPLSs and propose a family of q-rung picture linguistic Heronian mean operators, such as the q-rung picture linguistic Heronian mean (q-RPLHM) operator, the q-rung picture linguistic weighted Heronian mean (q-RPLWHM) operator, the q-rung picture linguistic geometric Heronian mean (q-RPLGHM) operator, and the q-rung picture linguistic weighted geometric Heronian mean (q-RPLWGHM) operator. The prominent advantage of the proposed operators is that the interrelationship between q-rung picture linguistic numbers (q-RPLNs) can be considered. Further, we put forward a novel approach to MAGDM based on the proposed operators. We also provide a numerical example to demonstrate the validity and superiorities of the proposed method. Full article
(This article belongs to the Special Issue Fuzzy Techniques for Decision Making 2018)
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Open AccessArticle Some Interval Neutrosophic Linguistic Maclaurin Symmetric Mean Operators and Their Application in Multiple Attribute Decision Making
Symmetry 2018, 10(4), 127; https://doi.org/10.3390/sym10040127
Received: 10 April 2018 / Revised: 15 April 2018 / Accepted: 17 April 2018 / Published: 22 April 2018
Cited by 1 | PDF Full-text (381 KB) | HTML Full-text | XML Full-text
Abstract
There are many practical decision-making problems in people’s lives, but the information given by decision makers (DMs) is often unclear and how to describe this information is of critical importance. Therefore, we introduce interval neutrosophic linguistic numbers (INLNs) to represent the less clear
[...] Read more.
There are many practical decision-making problems in people’s lives, but the information given by decision makers (DMs) is often unclear and how to describe this information is of critical importance. Therefore, we introduce interval neutrosophic linguistic numbers (INLNs) to represent the less clear and uncertain information and give their operational rules and comparison methods. In addition, since the Maclaurin symmetric mean (MSM) operator has the special characteristic of capturing the interrelationships among multi-input arguments, we further propose an MSM operator for INLNs (INLMSM). Furthermore, considering the weights of attributes are the important parameters and they can influence the decision results, we also propose a weighted INLMSM (WINLMSM) operator. Based on the WINLMSM operator, we develop a multiple attribute decision making (MADM) method with INLNs and some examples are used to show the procedure and effectiveness of the proposed method. Compared with the existing methods, the proposed method is more convenient to express the complex and unclear information. At the same time, it is more scientific and flexible in solving the MADM problems by considering the interrelationships among multi-attributes. Full article
(This article belongs to the Special Issue Fuzzy Techniques for Decision Making 2018)
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