Extended Cloud–TODIM Method for Multiple-Attribute Decision-Making Problems in Risk Reduction Schemes: Application in the Tailings Storage Facility Failure

Various tailings storage facility (TSF) failures have caused catastrophic consequences, such as life and property losses and environmental destruction. It is crucial to select the optimal risk reduction scheme (RRS) to guarantee the safety and stability of the TSF. Decision-making problems in RRS selection for TSF failure are multiple-attribute decision-making problems. During the RRS selection process, the psychological behavior of the decision makers should be considered. To solve such problems, the cloud–TODIM (abbreviation for interactive and multi-attribute decision-making in Portuguese) method is proposed for RRS selection in this paper. Firstly, the quantitative evaluation information is qualified and converted into clouds based on the cloud model, in which the characteristics of fuzziness, uncertainty, and randomness can be described. Secondly, an improved TODIM method is proposed to select the optimal RRS. Furthermore, a TSF is employed as a case study to examine the superiority of the proposed method. Finally, the sensitivity of the loss aversion coefficient θ, which reflects the attitudes of the decision makers (DMs) to the loss, is analyzed and a comparative analysis is developed therefore illustrating the competitiveness of the multiple-attribute decision-making of the proposed method.