scholarly journals Extension of VIKOR method for decision making problem with interval numbers

2009 ◽  
Vol 33 (5) ◽  
pp. 2257-2262 ◽  
Author(s):  
Mohammad Kazem Sayadi ◽  
Majeed Heydari ◽  
Kamran Shahanaghi
Keyword(s):  
Decision Making ◽  
Vikor Method ◽  
Interval Numbers ◽  
Decision Making Problem

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.

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.

Multi-attribute Group Decision-making (MAGDM) using Fuzzy Linguistic Modeling Integrated with the VIKOR Method for Car Purchasing Model

2022 ◽  
Vol 14 (1) ◽  
pp. 0-0
Keyword(s):  
Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Decision Making Process ◽  
Vikor Method ◽  
Decision Making Problem ◽  
Purchasing Model ◽  
The Individual ◽  
Fuzzy Linguistic

The change in the trend of transportation, increasing per capita income, expectation of better lifestyle, easy finance, and reduced cost of the automobile are some of the main factors that enable a commoner to have his/her own car. Therefore, it is essential to comprise such features in cars that offer qualities enabling the ease of consumer’s decision-making and comfort to purchase a car individually. Purchasing a car is a complicated multi-criteria decision-making problem as an individual may have different preferences for different criteria attributes. The attributes may be conflicting in nature depending on the need of the individual customer. Generally, it becomes quite difficult to assign ratings to these attributes based on numeric values. Therefore, the decision-making process relies on an idiosyncratic finding of the decision-makers which is in practice fuzzy with uncertainities. Hence, this article is a case study that deals with a hierarchy MCDM approach in accordance with the fuzzy logic and VIKOR method to solve a car purchasing problem.

scholarly journals Extension Dependent Degree Method with Mapping Transformation for Three-Parameter Interval Number Decision Making

2018 ◽  
Vol 2018 ◽  
pp. 1-12
Author(s):  
Li-Bo Xu ◽  
Xing-Sen Li ◽  
Jun-kai Shao ◽  
Kai-jie Wang
Keyword(s):  
Decision Making ◽  
Interval Mapping ◽  
Transformation Method ◽  
Interval Number ◽  
Interval Numbers ◽  
New Approach ◽  
Dependent Function ◽  
Optimal Value ◽  
Decision Making Problem ◽  
Parameter Interval

In view of the multiattribute decision making problem that the attribute values and weights are both three-parameter interval numbers, a new decision making approach and framework based on extension simple dependent degree are proposed. According to traditional extension simple dependent function, the new approach proposes a new extension dependent function for three-parameter interval number. Then through an interval mapping transformation method, the process for obtaining dependent degree for the interval with its optimal value not being the endpoint is transformed to the monotonous process for the interval with its optimal value being the endpoint. The method can not only perform uncertain analysis of decision results by different settings of attitude coefficients, but also take dynamic analysis and rule finding by some extension transformation. At last, an example is presented to examine the effectiveness and stability of our method.

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