scholarly journals An Approach to Solve Multi Attribute Decision-making Problem Based on the New Possibility Measure of Picture Fuzzy Numbers

2022 ◽  
Vol 10 (1) ◽  
pp. 153-159
Author(s):  
K. Deva ◽  
S. Mohanaselvi
Keyword(s):  
Decision Making ◽  
Fuzzy Numbers ◽  
Possibility Measure ◽  
Decision Making Problem ◽  
Multi Attribute Decision Making

scholarly journals A New Approach for Ranking Shadowed Fuzzy Numbers and its Application

2020 ◽  
Vol 12 (6) ◽  
pp. 17-32
Author(s):  
Mohamed A. H. El-Hawy
Keyword(s):  
Decision Making ◽  
Fuzzy Numbers ◽  
Standard Form ◽  
Decision Makers ◽  
New Method ◽  
New Approach ◽  
Decision Making Problem ◽  
Different Types ◽  
Multi Attribute Decision Making ◽  
The Comparative Study

In many decision situations, decision-makers face a kind of complex problems. In these decision-making problems, different types of fuzzy numbers are defined and, have multiple types of membership functions. So, we need a standard form to formulate uncertain numbers in the problem. Shadowed fuzzy numbers are considered granule numbers which approximate different types and different forms of fuzzy numbers. In this paper, a new ranking approach for shadowed fuzzy numbers is developed using value, ambiguity and fuzziness for shadowed fuzzy numbers. The new ranking method has been compared with other existing approaches through numerical examples. Also, the new method is applied to a hybrid multi-attribute decision making problem in which the evaluations of alternatives are expressed with different types of uncertain numbers. The comparative study for the results of different examples illustrates the reliability of the new method.

scholarly journals A Fuzzy Approach for Ranking Discrete Multi-Attribute Alternatives under Uncertainty

Mathematics ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 945 ◽  
Author(s):  
Lihui Liu ◽  
Hepu Deng
Keyword(s):  
Decision Making ◽  
Fuzzy Numbers ◽  
Pairwise Comparison ◽  
Fuzzy Approach ◽  
Attribute Importance ◽  
Decision Making Problem ◽  
Efficiency And Effectiveness ◽  
Multi Attribute Decision Making ◽  
Fuzzy Extent Analysis

This paper presents a fuzzy approach for ranking discrete alternatives in multi-attribute decision-making under uncertainty. Linguistic variables approximated by fuzzy numbers were applied for facilitating the making of pairwise comparison by the decision maker in determining the alternative performance and attribute importance using fuzzy extent analysis. The resultant fuzzy assessments were aggregated using the simple additive utility method for calculating the fuzzy utility of each alternative across all the attributes. An ideal solution-based procedure was developed for comparing and ranking these fuzzy utilities, leading to the determination of the overall ranking of all the discrete multi-attribute alternatives. An example is provided that shows the proposed approach is effective and efficient in solving the multi-attribute decision making problem under uncertainty, due to the simplicity and comprehensibility of the underlying concept and the efficiency and effectiveness of the computation involved.

scholarly journals A Multi-Attribute Decision-Making Algorithm Using Q-Rung Orthopair Power Bonferroni Mean Operator and Its Application

Mathematics ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 1240 ◽  
Author(s):  
Ping He ◽  
Zaoli Yang ◽  
Bowen Hou
Keyword(s):  
Decision Making ◽  
Influence Factors ◽  
Uncertain Information ◽  
Fuzzy Information ◽  
Bonferroni Mean ◽  
Decision Making Problem ◽  
Multi Attribute Decision Making ◽  
New Type ◽  
Multiple Variables ◽  
Internal Relationship

The process of decision-making is subject to various influence factors and environmental uncertainties, which makes decision become a very complex task. As a new type of decision processing tool, the q-rung orthopair fuzzy sets can effectively deal with complex uncertain information arising in the decision process. To this end, this study proposes a new multi-attribute decision-making algorithm based on the power Bonferroni mean operator in the context of q-rung orthopair fuzzy information. In this method, in view of multi-attribute decision-making problem of internal relationship between multiple variables and extreme evaluation value, the Bonferroni mean operator is combined with power average operator. Then, the integrated operator is introduced into the q-rung orthopair fuzzy set to develop a new q-rung orthopair power Bonferroni mean operator, and some relevant properties of this new operator are discussed. Secondly, a multi-attribute decision-making method is established based on this proposed operator. Finally, the feasibility and superiority of our method are testified via a numerical example of investment partner selection in the tourism market.

A multi-criteria decision-making method based on triangular interval-valued fuzzy numbers and the VIKOR method

2021 ◽  
Vol 40 (1) ◽  
pp. 221-233
Author(s):  
Xingang Wang ◽  
Ke Wang
Keyword(s):  
Decision Making ◽  
Fuzzy Numbers ◽  
Fuzzy Theory ◽  
Research Direction ◽  
Vikor Method ◽  
Connection Number ◽  
Criterion Weight ◽  
Decision Making Problem ◽  
Electre Method ◽  
Interval Valued

In many cases, complex problems cannot be accurately described by precise numerical values. Fuzzy theory provides a suitable tool for solving these problems. However, if decision makers cannot reach an agreement on the method for defining linguistic variables based on fuzzy sets, TIVFNs (triangular interval-valued fuzzy numbers) can provide more accurate modeling. Therefore, solving fuzzy MCGDM (multiple criteria group decision-making) problem with an unknown expert weight and criterion weight in TIVFNs has become an important research direction. In this paper, TIVF-VIKOR (triangular interval-valued fuzzy VIKOR) method, which is suitable for the environment of TIVFNs, is proposed to solve the problem of fuzzy MCGDM. To achieve this goal, the TIVF-VIKOR method is innovatively adopted similarity and coefficient of variation are combined to calculate expert weight, and deviation maximization method based on divergence matrix is used to calculate criterion weight. VIKOR method is used to find the compromise solutions, which are converted into the form of binary connection number, and the optimal compromise solution is obtained after ranking. The proposed method is applied to the problem of machine fault detection, and the validity and feasibility of the method are illustrated. Compared with the TOPSIS∖ELECTRE method, the ranking results of the three methods are equivalent, and the fluctuation of the TIVF-VIKOR method is more distinct.

Method for Fuzzy Multi-Attribute Decision-Making with Fuzzy Reciprocal Preference Relation on Alternatives under Partical Weight Information

2011 ◽  
Vol 58-60 ◽  
pp. 869-874
Author(s):  
Hong An Zhou
Keyword(s):  
Decision Making ◽  
Fuzzy Numbers ◽  
Programming Model ◽  
Preference Relation ◽  
Triangular Fuzzy Numbers ◽  
Attribute Weights ◽  
Translation Function ◽  
Goal Programming Model ◽  
Subjective Preference ◽  
Multi Attribute Decision Making

The fuzzy multi-attribute decision-making (FMADM) problems, in which the information about attribute weights is partly known, the attribute values take the form of triangular fuzzy numbers, and the decision maker (DM) has fuzzy reciprocal preference relation on alternatives, are investigated. Firstly, some concepts, such as the multiply between two triangular fuzzy numbers, the projection of triangular fuzzy numbers vectors, etc, are given. Secondly, in order to reflect to the DM’s subjective preference information on alternatives, we make the objective decision information uniform by using a translation function and establish a goal programming model, and then the attribute weights is obtained by solving the model, thus the weighted attribute values of all alternatives are gained. The concept of fuzzy positive ideal solution (FPIS) of alternatives is introduced, and the alternatives are ranked by using the projection of the weighted attribute values of every alternative on FPIS. The method not only can sufficiently utilize the objective information and meet the DM’s subjective preferences on alternatives as much as possible, but also it is characterized by simple operation and easy to implement on a computer. Finally, a practical example is illustrated to show the feasibility and availability of the developed method.

EXTENDED INDUCED ORDERED WEIGHTED AVERAGING DISTANCE OPERATORS AND THEIR APPLICATION TO GROUP DECISION-MAKING

2013 ◽  
Vol 12 (04) ◽  
pp. 789-811 ◽  
Author(s):  
SHOUZHEN ZENG ◽  
WEI LI ◽  
JOSÉ M. MERIGÓ
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Numbers ◽  
Group Decision ◽  
Weighted Averaging ◽  
Interval Numbers ◽  
Ordered Weighted Averaging ◽  
Special Cases ◽  
Decision Making Problem ◽  
Available Information

The induced ordered weighted averaging distance (IOWAD) approach is very suitable in situations in which the available information is represented with exact numerical values. In this paper, we develop some extended IOWAD operators: the linguistic induced ordered weighted averaging distance (LIOWAD) operator, the uncertain induced ordered weighted averaging distance (UIOWAD) operator and the fuzzy induced ordered weighted averaging distance (FIOWAD) operator. Their main objective is to assess uncertain situations in which the available information is given in the form of linguistic variables, interval numbers and fuzzy numbers. Some special cases of these three new extensions are studied. Finally, we develop an application of the new operators in a group decision-making problem under an uncertain environment and illustrate it with a numerical example.

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