Decision Making of Construction Risk Control Scheme for Foundation Pit Based on Prospect-Evidence Theory Under Incomplete Information Conditions

Owing to various uncertainty factors during the construction process, foundation pit engineering is prone to crisis situations and various risks, and thus quick and rational decisions on construction risk control options must be made. In response to the phenomenon that the evaluation values of certain indicators in the decision making of deep foundation pit support schemes may be missing, this paper proposes a decision making method for construction risk control schemes that combines prospect theory with evidence theory. The method establishes a prospect decision matrix based on a decision indicator system for deep foundation pit construction risk control schemes, taking the decision maker’s desired goal for the project as the reference point; the indicator prospect values of each scheme are then used as evidence, and the belief intervals of all schemes are obtained through evidence synthesis to serve as the basis for scheme decision making. This method enriches the existing theoretical framework for the decision making of engineering construction risk control schemes. Compared with existing decision models, the decision method proposed in this paper exhibits the following distinctive features: First, the method accommodates decision situations in which some attribute evaluation values are missing, without requiring the missing values to be interpolated with precise values, fuzzy numbers, interval numbers, or probability distributions, and without necessarily discarding the decision attributes containing missing values, reflecting its better decision adaptability. Second, the degree of information incompleteness, i.e., the number of missing values, is intuitively reflected in the decision results, demonstrating the method’s better information fidelity and model interpretability. Third, the method incorporates behavioral factors such as the target expectation and risk attitude of the decision maker into the decision making process, and can objectively reveal the influence of these factors on the decision results through sensitivity analysis, thereby providing a basis for the decision maker to select the decision results more rationally. Combined with the analysis of a large-scale underground pit project, the results show that this method is not constrained by the completeness or incompleteness of the evaluation information of the indicators, and by taking the decision maker’s reasonable expectation as the reference point, it proves more reasonable than methods that take the absolute optimum or the worst value as the ideal reference point for scheme decision making. The method developed in this study can be applied to the decision making of risk control schemes in similar underground engineering or other civil engineering projects.