Affiliations:
School of Economics and Management, North China Electric Power University, Beijing, China
Correspondence:
[*]
Corresponding author. Feng Xia, School of Economics and Management, North China Electric Power University,
Beijing 102206, China. E-mail: [email protected].
Abstract: In this paper, we give a risky decision-making approach based on prospect theory and cloud theory to solve the wind power investment problem. In this problem, the criteria value of alternative is linguistic assessment information and the criteria’s weights are partially known. Firstly, we use the cloud theory to transfer the linguistic variables into one-dimensional normal cloud model. On the basis of defining the normal cloud model comparison rule and viewing all other alternatives as the reference point, a cloud prospect value function can be defined. Then, the cloud prospect decision-making matrix can be attained. Secondly, to get the optimal criteria weights, an optimization programming model which satisfies the algorithm of maximizing deviation and the decision makers’ subjective information is enacted. After that, we aggregate the clouds of each alternative as a comprehensive cloud. Then the order of alternatives can be listed by comparing comprehensive cloud of each alternative. Finally, an illustrative example about wind power investment is given and we verify the effectiveness and feasibility of this approach which can be valuable in the wind power investment decision-making.
Keywords: Wind power investment, risky decision making, linguistic assessment, maximizing deviation
