Dynamic Multi-attribute Decision Making model based on intuitionistic trapezoidal fuzzy numbers

Author(s):  
Yuwen Shi
2015 ◽  
Vol 14 (4) ◽  
pp. 11-28 ◽  
Author(s):  
Wei Lin ◽  
Guangle Yan ◽  
Yuwen Shi

Abstract In this paper we investigate the dynamic multi-attribute group decision making problems, in which all the attribute values are provided by multiple decision makers at different periods. In order to increase the level of overall satisfaction for the final decision and deal with uncertainty, the attribute values are enhanced with generalized interval-valued trapezoidal fuzzy numbers to cope with the vagueness and indeterminacy. We first define the Dynamic Generalized Interval-valued Trapezoidal Fuzzy Numbers Weighted Geometric Aggregation (DGITFNWGA) operator and give an approach to determine the weights of periods, using the probability density function of Gamma distribution, and then a dynamic multi-attribute group decision making method is developed. The method proposed employs the Generalized Interval-valued Trapezoidal Fuzzy Numbers Hybrid Geometric Aggregation (GITFNHGA) operator to aggregate all individual decision information into the collective attribute values corresponding to each alternative at the same time period, and then utilizes the DGITFNWGA operator to aggregate the collective attribute values at different periods into the overall attribute values corresponding to each alternative and obtains the alternatives ranking, by which the optimal alternative can be determined. Finally, an illustrative example is given to verify the approach developed.


2021 ◽  
Author(s):  
Kavitha Koppula ◽  
Babushri Srinivas Kedukodi ◽  
Syam Prasad Kuncham

AbstractWe define $$2n+1$$ 2 n + 1 and 2n fuzzy numbers, which generalize triangular and trapezoidal fuzzy numbers, respectively. Then, we extend the fuzzy preference relation and relative preference relation to rank $$2n+1$$ 2 n + 1 and 2n fuzzy numbers. When the data is representable in terms of $$2n+1$$ 2 n + 1 fuzzy number, we generalize the FMCDM (fuzzy multi-criteria decision making) model constructed with TOPSIS and relative preference relation. Lastly, we give an example from telecommunications to present the proposed FMCDM model and validate the results obtained.


2021 ◽  
Vol 236 ◽  
pp. 05036
Author(s):  
Wen Mi ◽  
Wen Jing ◽  
Wu Xiao-feng ◽  
Zhang Yi-ming ◽  
Fang Qiang

This paper puts forward the concept of incentive utility, which converts the value of each attribute in multi-attribute decision-making into a unified index for measurement, thus simplifying multi-attribute decision-making. In this paper, a comprehensive evaluation model based on the TOPSIS of incentive utility is established. Through the establishment of incentive index, the utility of incentive and the calculation of ideal point of utility, the disadvantage of "ideal point is not ideal" in the TOPSIS is overcome. It can better synthesize the sub-attribute value and realize the subjective multi-attribute decision-making. The example shows that the model can apply subjective factors to decision-making scientifically, and the result is more reasonable and effective.


Sign in / Sign up

Export Citation Format

Share Document