Paper Info
Title
A multistage risk decision making method for normal cloud model considering behavior characteristics.
Abstract
It is difficult to make scientific decisions for multistage risk decision-making problems, which are mainly influenced by these challenges, such as uncertainty of information, the passage of time and complexity of the problems The multistage risk decision-making problem is analyzed for normal cloud model considering behavior characteristics in this paper. Firstly, considering the fuzziness and randomness of multi-stage risk decision-making information, the relative entropy and modified relative entropy are defined as the distance measures for the normal cloud model from the perspective of full utilization of information. Secondly, the prospect theory is extended to normal cloud model environment. Considering the behavior characteristics of reference dependence, two reference points are set up considering the short-term development and long-term development. Thirdly, the optimization model is built to obtain the attribute weights and stage weights based on the principle of maximizing the difference between ranking values. The ranking of alternatives is determined by the final ranking values. The case analysis and the method comparison illustrate the feasibility and rationality of the proposed method.
Year
DOI
Venue
2019
10.1016/j.asoc.2019.02.033
Applied Soft Computing
Keywords
Field
DocType
Multistage risk decision making,Normal cloud model,Prospect theory,Reference dependence,Relative entropy
Mathematical optimization,Rationality,Ranking,Prospect theory,Kullback–Leibler divergence,Mathematics,Cloud computing,Randomness,Distance measures,Case analysis
Journal
Volume
ISSN
Citations 
78
1568-4946
1
PageRank 
References 
Authors
0.37
0
2
Name
Order
Citations
PageRank
Wen Song145.13
Zhu Jian-jun2543.84