TMT group decision method based on system dynamics and game control theory

Abstract Trapezoidal cubic fuzzy numbers (TzCFNs) are an extraordinary cubic fuzzy set on a real number set. TzCFNs are useful for dealing with well-known quantities in decision data and decision making problems themselves. This paper is about multi-attribute group decision making problems in which the attribute values are stated with TzCFNs, which are solved by developing a new decision method based on power average operators of TzCFNs. The new operation laws for TzCFNs are given. Hereby, the power average operator of real numbers is extended to four kinds of power average operators of TzCFNs, involving the power average operator of TzCFNs, the weighted power average operator of TzCFNs, the power ordered weighted average operator of TzCFNs, and the power hybrid average operator of TzCFNs. In the proposed group decision method, the individual overall evaluation values of alternatives are generated by using the power average operator of TzCFNs. Applying the hybrid average operator of TzCFNs, the specific general evaluation standards of alternatives are then combined into the collective ones, which are used to rank the alternatives. The example analysis shows the practicality and effectiveness of the proposed method.

Download Full-text

A Grey Target Group Decision Method with Dual Hesitant Fuzzy Information considering Decision-Maker’s Loss Aversion

Scientific Programming ◽

10.1155/2020/8930387 ◽

2020 ◽

Vol 2020 ◽

pp. 1-10

Author(s):

Yufeng Zhou ◽

Yufeng Li ◽

Zhi Li

Keyword(s):

Loss Aversion ◽

Group Decision ◽

Target Group ◽

Fuzzy Information ◽

Attribute Weights ◽

Decision Method ◽

Fuzzy Environment ◽

Proposed Model ◽

Fuzzy Ideal ◽

Behavioral Preference

The uncertainty, complexity, and behavioral preference are widely existing in real-world decision-making problems. In this paper, different from the previous grey target decision method, we propose a novel grey target group decision method considering decision-maker’s loss aversion with positive and negative clouts under the dual hesitant fuzzy environment. Firstly, defining the dual hesitant fuzzy ideal optimization scheme as the positive clout and the ideal inferior scheme as the negative clout, positive and negative target-eye distances are measured by the normalized Hamming distances from the DHFEs to the positive clout and the negative clout. Then, a new comprehensive target-eye distance is proposed to evaluate alternatives between the positive and the negative clout. A nonlinear optimization model is established to obtain the optimal initial attribute weights with the goal of minimizing the comprehensive target-eye distance. Then, a grey target group decision method with dual hesitant fuzzy information considering decision-maker’s loss aversion and variable weights is proposed. Finally, a numeral example is given to verify the effectiveness and practicality of the proposed model and method.

Download Full-text