Multi-Attribute Decision-Making Method Based on Prospect Theory in Heterogeneous Information Environment and Its Application in Typhoon Disaster Assessment

Abstract

Aiming at the decision-making problem in heterogeneous information environment and considering the influence of decision makers' psychological behavior on decision-making results, this paper proposes a multi-attribute decision-making method based on prospect theory in heterogeneous information environment. The heterogeneous information in this paper indicates that the decision attribute value is represented by various types of data forms, including exact number, interval number, linguistic term, intuitionistic fuzzy number, interval intuitionistic fuzzy number, neutrosophic numbers, and trapezoidal fuzzy neutrosophic numbers, and so on. Firstly, the distance and similarity measure of various heterogeneous data are introduced, and the heterogeneous information attribute weights are obtained using the deviation maximization method. Then, the psychological expectation value of each attribute given by the decision maker is used as a reference point, thereby calculating the gain and loss of each attribute value relative to the reference point, and establishing a gain matrix and a loss matrix. On this basis, the prospect theory is used to obtain the comprehensive prospect value of each alternative, so as to obtain the alternative ordering result and optimal alternative. Finally, an illustrative example about typhoon disaster assessment is presented to show the feasibility and effectiveness of the proposed method, and the advantages of the proposed method are illustrated by comparison with other methods.

An Emergency Decision-Making Method for Coal Spontaneous Combustion Based on Improved Prospect Theory

“…According to previous studies [39], even when the weight information is completely unknown and all decision maker preference coefficients exceed 0.2, the optimal solution remains unaffected. In this study, all preference coefficients of decision makers exceeded 0.2, and our findings support those reported in the literature [44,48]. This suggests that the decision outcomes in this study are independent of the decision maker's preference coefficients (α, β, θ), possibly due to their adoption of similar reference points.…”

Decision-making method based on game theory and grey theory in a single-value neutrosophic environment and its application to typhoon disaster assessment

“…More recently, FSs, IFSs and NSs have been used for TDA. For example, He (2018) proposed a TDA method based on Dombi aggregation operators with hesitant fuzzy numbers, Li et al (2015) suggested one based on TOPSIS with intuitionistic fuzzy numbers, Yu's (2015) is based on generalized intuitionistic fuzzy aggregation operators with intuitionistic fuzzy numbers, Tan et al (2018) studied TDA based on the exponential aggregation operator with interval value neutrosophic numbers, Tan et al (2019) proposed a TDA method based on prospect theory with heterogeneous information including neutrosophic numbers, Tan et al (2020) analysed TDA based on GRA under double incomplete information with trapezoidal fuzzy neutrosophic numbers, Tan et al (2021) put forward a TDA method based on new entropy with refined SVNN, Tan et al (2020b) proposed another TDA method based on DEMATEL and fuzzy distance with trapezoidal fuzzy neutrosophic numbers and Wu et al (2020) proposed a TDA method based on public safety triangle theory. TDA has the properties of timeliness, complexity and uncertainty, which makes it suitable for using neutrosophic numbers to represent disaster assessment information.…”

Application of multi-attribute decision-making methods based on normal random variables in supply chain risk management

“…Therefore, the normal interval number is more accurate and reasonable in reflecting decision information [3]. As can be seen from the normal interval number β = ⟨{0.82, 0.13}, 0.75, 0.20⟩, the decision maker believes that the degree of evaluation object belonging to {0.82, 0.13} is 0.75, while the degree of not belonging to {0.82, 0.13} is 0.20, and the degree of hesitation that cannot be determined whether it belongs to {0.82, 0.13} is 0.05 [4].…”