Affiliations: [a] School of Economics and Management, North China Electronic Power University, Beijing, China | [b] School of Mathematics Science, Inner Mongolia University, Huhehaote, Inner Mongolia, China
Correspondence:
[*]
Corresponding author: Zhi-Qiang Qi, School of Economics and Management, North China Electronic Power University, Beijing 102206, China. Tel.: +86 15901336028; Fax: +86 010 80796904; E-mail:[email protected]
Abstract: We propose a decision-making approach based on the
prospect theory and the cloud model for risky multi-criteria decision-making
problem in which the criteria value of alternatives are uncertain and the
linguistic variables and criteria's weights are partially unknown. In this
method, the linguistic variables are converted into a cloud model. To
address the shortcomings of the existing cloud generating method, a new
method is developed based on the golden segmentation ratio and the cloud's
rule of `3En'. And then, another method for measuring the distance among
clouds and the degree of possibility of the cloud model is given to apply
Prospect Theory to the linguistic environment. Furthermore, the treatment of
other alternative solutions as dynamic reference points is considered. Based
on the algorithm of maximizing deviation, the optimal model balances the
subjective and objective information and through this model, the optimal
criteria weights and the integrated prospect value of each solution are
obtained. Finally, these solutions are ordered on the principle that the
bigger the integrated prospect value is, the more optimal the solution will
be. At the end of this paper, we use an example to examine the rationality
and reliability of the given method.
Keywords: Risky decision-making, cloud model, prospect theory, maximum deviation
