Three-Way Decisions Based on Q-Rung Orthopair Fuzzy 2-Tuple Linguistic Sets with Generalized Maclaurin Symmetric Mean Operators

As a typical model of three-way decisions (3WD), decision-theoretic rough sets (DTRS), have gained attention from scholars in decision-making problems. The q-rung orthopair fuzzy 2-tuple linguistic variable (QROF2-TLV) is a mixture of two different notions, q-rung orthopair fuzzy sets (QROFS) and 2-tuple linguistic variables (2-TLV), and is an extensive and proficient technique for coping with awkward and complicated information in realistic decision-making. In this paper, we first propose a DTRS model for 3WD based on QROF2-TLV that gives a new method for evaluating loss functions (LF) of DTRS. We further present the q-rung orthopair fuzzy 2-tuple linguistic generalized Maclaurin symmetric mean (QROF2-TLGMSM) and weighted QROF2-TLGMSM operators and then provide the LFs of DTRS based on QROF2-TLV with the values aggregated by the QROF2-TLGMSM operator. Thus, we propose the q-rung orthopair fuzzy 2-tuple linguistic variable DTRS (QROF2-TLV-DTRS) model. Subsequently, a technique for concluding another DTRS model, which can give the related semantic translation of the decision consequences of every other option, is presented. The model is applied to expound the proposed technique in detail, and the impacts of various conditional probabilities on decision outcomes are discussed. A comparative analysis of the proposed approach is also conducted to examine the proficiency of the proposed method.

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Multiple Attribute Decision-Making Methods with Unbalanced Linguistic Variables Based on Maclaurin Symmetric Mean Operators

International Journal of Information Technology & Decision Making ◽

10.1142/s0219622018500013 ◽

2019 ◽

Vol 18 (01) ◽

pp. 105-146 ◽

Cited By ~ 6

Author(s):

Fei Teng ◽

Peide Liu ◽

Li Zhang ◽

Juan Zhao

Keyword(s):

Decision Making ◽

Multiple Attribute Decision Making ◽

Aggregation Operators ◽

Linguistic Variables ◽

Numerical Example ◽

Maclaurin Symmetric Mean ◽

Multiple Attribute ◽

Linguistic Term

In this paper, we firstly introduced the unbalanced linguistic term sets, the linguistic transforming methodology, the Maclaurin symmetric mean (MSM) operator and dual MSM (DMSM) operator. Then, we proposed the closed operational rules of unbalanced linguistic variables, and several new MSM aggregation operators, including unbalanced linguistic MSM (ULMSM) operator, weighted unbalanced linguistic MSM (WULMSM) operator, unbalanced linguistic DMSM (ULDMSM) operator and weighted unbalanced linguistic DMSM (WULDMSM) operator. Further, we proposed two multiple attribute decision-making (MADM) methods under unbalanced linguistic environments based on the WULMSM operator and WULDMSM operator, respectively. Finally, a numerical example is used to show the applicability and effectiveness of the proposed MADM methods and to reveal their advantages by comparing with the existing methods.

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Some Novel Picture 2-Tuple Linguistic Maclaurin Symmetric Mean Operators and Their Application to Multiple Attribute Decision Making

Symmetry ◽

10.3390/sym11070943 ◽

2019 ◽

Vol 11 (7) ◽

pp. 943

Author(s):

Min Feng ◽

Yushui Geng

Keyword(s):

Decision Making ◽

Fuzzy Set ◽

Multiple Attribute Decision Making ◽

Aggregation Operators ◽

Linguistic Variable ◽

Maclaurin Symmetric Mean ◽

Multiple Attribute ◽

Picture Fuzzy Set ◽

Input Parameters ◽

Cognitive Information

When solving multiple attribute decision making (MADM) problems, the 2-tuple linguistic variable is an effective tool that can not only express complex cognitive information but also prevent loss of information in calculation. The picture fuzzy set (PFS) has three degrees and has more freedom to express cognitive information. In addition, Archimedean t-conorm and t-norm (ATT) can generalize most existing t-conorms and t-norms and Maclaurin symmetric mean (MSM) operators can catch the relationships among the multi-input parameters. Therefore, we investigate several novel aggregation operators, such as the picture 2-tuple linguistic MSM (2TLMSM) operator based on the ATT (ATT-P2TLMSM) and the picture 2-tuple linguistic generalized MSM (2TLGMSM) operator based on ATT (ATT-P2TLGMSM). Considering that the input parameters have different importance, we proposed picture 2-tuple linguistic weighted MSM (2TLWMSM) operators based on ATT (ATT-P2TLWMSM) and picture 2-tuple linguistic weighted generalized MSM (2TLWGMSM) operators based on ATT (ATT-P2TLWGMSM). Finally, a MADM method is introduced, and an expositive example is presented to explain the availability and applicability of the developed operators and methods.

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THREE-WAY GOVERNMENT DECISION ANALYSIS WITH DECISION-THEORETIC ROUGH SETS

International Journal of Uncertainty Fuzziness and Knowledge-Based Systems ◽

10.1142/s0218488512400090 ◽

2012 ◽

Vol 20 (supp01) ◽

pp. 119-132 ◽

Cited By ~ 82

Author(s):

DUN LIU ◽

TIANRUI LI ◽

DECUI LIANG

Keyword(s):

Rough Set ◽

Rough Sets ◽

Decision Procedure ◽

Loss Functions ◽

Conditional Probabilities ◽

Bayesian Decision ◽

Government Decision ◽

Risk Investment ◽

Negative Rule

By considering the risks in policy making procedure, a three-way decision approach based on the decision-theoretic rough set model is adopted to risk government decision-making. A three-way decision is made based on a pair of thresholds on conditional probabilities. A positive rule makes a decision of executing, a negative rule makes a decision of non-executing, and a boundary rule makes a decision of deferment. The loss functions are used to calculate the required two thresholds to describe the decision risk with the Bayesian decision procedure. A case study of government petroleum risk investment demonstrates the proposed method.

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Some Maclaurin Symmetric Mean Aggregation Operators Based on Cloud Model and Their Application to Decision-Making

International Journal of Information Technology & Decision Making ◽

10.1142/s0219622019500135 ◽

2019 ◽

Vol 18 (03) ◽

pp. 981-1007 ◽

Cited By ~ 2

Author(s):

Peide Liu ◽

Hongyu Yang ◽

Haiquan Wu ◽

Meilong Ju ◽

Fawaz E. Alsaadi

Keyword(s):

Decision Making ◽

Quantitative Method ◽

Group Decision ◽

Cloud Model ◽

Aggregation Operators ◽

Linguistic Variables ◽

Qualitative Information ◽

New Approach ◽

Maclaurin Symmetric Mean ◽

Magdm Problems

The cloud model (CM) is an important tool to describe qualitative concept by the quantitative method, and the Maclaurin symmetric mean (MSM) can capture the interrelationship among the multi-inputs and it can generalize most of existing operators. In this paper, we firstly convert the uncertain linguistic variables (ULVs), which are easily used to express the qualitative information, to CM. Then, we combine the MSM with the CM, and propose the cloud MSM (CMSM) operator and cloud weighted MSM (CWMSM) operator. In addition, we explore some of their desirable features and develop a new approach to deal with some multi-attribute group decision-making (MAGDM) problems under the uncertain environment based on the proposed operators. Finally, by comparing with other approaches, an illustrative example is arranged to demonstrate the usability of the proposed method.

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Three-Way Decisions Making Using Covering Based Fractional Orthotriple Fuzzy Rough Set Model

Mathematics ◽

10.3390/math8071121 ◽

2020 ◽

Vol 8 (7) ◽

pp. 1121 ◽

Cited By ~ 3

Author(s):

Shougi S. Abosuliman ◽

Saleem Abdullah ◽

Muhammad Qiyas

Keyword(s):

Decision Making ◽

Rough Set ◽

Rough Sets ◽

Fuzzy Numbers ◽

Loss Functions ◽

Multi Criteria Decision Making ◽

Expected Loss ◽

Fuzzy Rough Set ◽

Decision Method ◽

Proposed Model

On the basis of decision-theoretical rough sets (DTRSs), the three-way decisions give new model of decision approach for deal with the problem of decision. This proposed model of decision method is based on the loss function of DTRSs. First, the concept of fractional orthotriple fuzzy β -covering (FOF β -covering) and fractional orthotriple fuzzy β -neighborhood (FOF β -neighborhood) was introduced. We combined loss feature of DTRSs with covering-based fractional orthotriple fuzzy rough sets (CFOFSs) under the fractional orthotriple fuzzy condition. Secondly, we proposed a new FOF-covering decision-theoretical rough sets model (FOFCDTRSs) and developed related properties. Then, based on the grade of positive, neutral and negative membership of fractional orthotriple fuzzy numbers (FOFNs), five methods are established for addressing the expected loss expressed in the form of FOFNs and the corresponding three-way decisions are also derived. Based on this, we presented a FOFCDTRS-based algorithm for multi-criteria decision making (MCDM). Then, an example verifies the feasibility of the five methods for solving the MCDM problem. Finally, by comparing the results of the decisions of five methods with different loss functions.

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Application of linguistic/non-numeric fuzzy aggregation to the ranking of processed crops

Tanzania Journal of Science ◽

10.4314/tjs.v47i2.26 ◽

2021 ◽

Vol 47 (2) ◽

pp. 710-717

Author(s):

David Koloseni

Keyword(s):

Decision Making ◽

Customer Satisfaction ◽

Linguistic Variable ◽

Linguistic Variables ◽

Crop Processing ◽

High Ranking ◽

Fuzzy Aggregation ◽

Product Technology ◽

Technology Marketing ◽

Selection Of

A non-numeric fuzzy aggregation approach is applied for the fusion of information obtained from farmers and experts for evaluation and selection of alternatives under multiple criteria. The technique has the ability to assign linguistic variable to fused information and find consensus of gathered opinions from a number of experts on crop processing for each processed crop. The technique is illustrated with a crop processing problem by adding value to the crop and increase income to entrepreneurs. The proposed technique has been successfully applied to the ranking of the processed crops based on the expert’s opinions, thus obtaining best preferences based on product, technology, marketing, and customer satisfaction. Five crops, namely beans, maize, rosella, sunflower and rice were ranked. Out of the five ranked crops, two processed crops (maize and sunflower) obtained high ranking. Keywords: Linguistic variables, Fuzzy aggregation, Processed crops, Decision making

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The dependence of the majority voting decision-making probabilities on a multi-expert binary system experts number

Informatization and communication ◽

10.34219/2078-8320-2020-11-1-7-14 ◽

2020 ◽

pp. 7-14

Author(s):

E. D. Avedyan ◽

Le Thi Trang Linh

Keyword(s):

Decision Making ◽

Binary System ◽

Conditional Probability ◽

Majority Voting ◽

Correct Solution ◽

Conditional Probabilities ◽

Analytical Results ◽

Independent Expert ◽

Mutually Independent

The article presents the analytical results of the decision-making by the majority voting algorithm (MVA). Particular attention is paid to the case of an even number of experts. The conditional probabilities of the MVA for two hypotheses are given for an even number of experts and their properties are investigated depending on the conditional probability of decision-making by independent experts of equal qualifications and on their number. An approach to calculating the probabilities of the correct solution of the MVA with unequal values of the conditional probabilities of accepting hypotheses of each statistically mutually independent expert is proposed. The findings are illustrated by numerical and graphical calculations.

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Dimensional Analysis under Linguistic Pythagorean Fuzzy Set

Symmetry ◽

10.3390/sym13030440 ◽

2021 ◽

Vol 13 (3) ◽

pp. 440

Author(s):

Aldo Joel Villa Silva ◽

Luis Pérez-Domínguez ◽

Erwin Martínez Gómez ◽

David Luviano-Cruz ◽

Delia Valles-Rosales

Keyword(s):

Decision Making ◽

Dimensional Analysis ◽

Fuzzy Set ◽

Multi Criteria Decision Making ◽

Linguistic Variables ◽

Mutual Relationship ◽

Pythagorean Fuzzy Set ◽

Cnc Router ◽

Selection Of

Dimensional analysis under linguistic Pythagorean fuzzy set (DA-LPFS) is a technique to handle qualitative (intangible) as well as the interactions between criteria, by combining dimensional analysis (DA) and Pythagorean fuzzy set (PFS) with linguistic variables. In this paper, a novel DA method is proposed for LPFSs based in a PFS extension, in order to consider the mutual relationship among criteria and handle qualitative (fuzzy) and quantitative (crisp) information usually involved in Multi-criteria decision making (MCDM) problems. Finally, DA-LPFS is applied to handle a case concerning the selection of CNC router to illustrate the applicability of the method.

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Extended VIKOR-QUALIFLEX Method Based on Trapezoidal Fuzzy Two-Dimensional Linguistic Information for Multiple Attribute Decision-Making with Unknown Attribute Weight

Mathematics ◽

10.3390/math9010037 ◽

2020 ◽

Vol 9 (1) ◽

pp. 37

Author(s):

Ye Li ◽

Yisheng Liu

Keyword(s):

Decision Making ◽

Qualitative Evaluation ◽

Multiple Attribute Decision Making ◽

Two Dimensional ◽

Linguistic Variables ◽

Linguistic Information ◽

Attribute Weight ◽

Model Based ◽

Subjective Weight ◽

Multiple Attribute

Considering the advantages of trapezoid fuzzy two-dimensional linguistic variables (TrF2DLVs), which can not only accurately describe the qualitative evaluation but also use qualitative linguistic variables (LVs) to describe the confidence level of this evaluation in the second dimension, this paper proposes a novel method based on trapezoidal fuzzy two-dimensional linguistic information to solve multiple attribute decision-making (MADM) problems with unknown attribute weight. First, a combination weight model is constructed, which covers a subjective weight determination model based on the proposed trapezoidal fuzzy two-dimensional linguistic best-worst method (TrF2DL-BWM) and an objective weight determination model based on the proposed CRITIC method. Then, in order to accurately rank the alternatives, an extended VIKOR-QUALIFLEX method is proposed, which can measure the concordance index of each ranking combination by means of group utility and individual maximum regret value of each evaluation alternative. Finally, a practical problem of lean management assessment for industrial residential projects is solved by the proposed method, and the effectiveness and advantages of the method are demonstrated by comparative analysis and discussion.

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Chameleonic knowledge: a study of ex ante analysis in large infrastructure policy processes

Policy Sciences ◽

10.1007/s11077-021-09423-5 ◽

2021 ◽

Author(s):

Lars Dorren ◽

Wouter Van Dooren

Keyword(s):

Decision Making ◽

Decision Makers ◽

Policy Outcomes ◽

Knowledge Use ◽

Short Term ◽

Cost Overruns ◽

Substantive Content ◽

Infrastructure Policy ◽

Decision Outcomes ◽

Ex Ante

AbstractUsing ex ante analysis to predict policy outcomes is common practice in the world of infrastructure planning. However, accounts of its uses and merits vary widely. Advisory agencies and government think tanks advocate this practice to prevent cost overruns, short-term decision-making and suboptimal choices. Academic studies on knowledge use, on the other hand, are critical of how knowledge can be used in decision making. Research has found that analyses often have no impact at all on decision outcomes or are mainly conducted to provide decision makers with the confidence to decide rather than with objective facts. In this paper, we use an ethnographic research design to understand how it is possible that the use of ex ante analysis can be depicted in such contradictory ways. We suggest that the substantive content of ex ante analysis plays a limited role in understanding its depictions and uses. Instead, it is the process of conducting an ex ante analysis itself that unfolds in such a manner that the analysis can be interpreted and used in many different and seemingly contradictory ways. In policy processes, ex ante analysis is like a chameleon, figuratively changing its appearance based on its environment.

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