### Establishment of Multi-Objective Optimization Evaluation System  
There is a large number and wide distribution range of the Pareto optimal solution set of the multi-objective optimization model. Each Pareto solution can meet the requirements of foundation pit dewatering. Therefore, the Analytic Hierarchy Process [27] (AHP) combined with the evaluation scoring method can be used to establish the evaluation system, so as to select the candidate set with high score in the Pareto solution set as the decision basis. The most important step for evaluation and decision making is to determine the weight and scoring standard of the sub-target layer (total dewatering cost, settlement influence coefficient, and safety and stability of the foundation pit structure).  
The evaluation system based on the multi-objective optimization model of dewatering is structured into two layers. The first layer, denoted as A, represents the main objective of optimizing the foundation pit dewatering. The second layer, referred to as the sub-target layer, includes three components: total dewatering cost (A1), settlement influence coefficient (A2), and safety and stability of the foundation pit structure (A3).  
According to the dewatering optimization experience, combined with the Saaty scale table [28], the weight judgment among sub-target layers is carried out, and the judgment matrix A is constructed. The maximum eigenvalue and corresponding eigenvector of the judgment matrix are calculated according to Equation (13):  
\[AW=\lambda_{max}W \tag{13}\]  
where \(W\) is the weight corresponding to the sub-target layer, and \(\lambda_{max}\) is the maximum eigenvalue of the judgment matrix.  
In order to avoid the influence of human subjective factors, it is necessary to carry out the consistency test on the constructed judgment matrix and calculate the consistency index \(C.I.\) of the judgment matrix and the consistency ratio \(C.R.\) Generally, when \(C.R.<0.1\), the consistency of the constructed judgment matrix can pass the test.  
\[C.I.=\frac{\lambda_{max}-n}{n-1} \tag{14}\]  
\[C.R.=\frac{C.I.}{R.I.} \tag{15}\]  
where \(n\) is the order of the constructed judgment matrix; \(C.I.\) is a consistency index; \(C.R.\) is the consistency ratio; and \(R.I.\) is the average random consistency index.  
Therefore, it is seen from Table 1 that the judgment matrix of the total dewatering cost, the settlement influence coefficient, and the safety and stability of the foundation pit structure on the total target A in the sub-target layer is constructed, and the weight and normalized weight corresponding to the sub-target layer are calculated according to Equation (13).  
\begin{table}
\begin{tabular}{c c c c c c} \hline
**A** & **A1** & **A2** & **A3** & \(\mathbf{W_{0}}\) & \(\mathbf{W_{0}}\) Normalization \\ \hline A1 & 1 & 1/3 & 1/5 & 0.492 & 0.109 \\ A2 & 3 & 1 & 1/2 & 1.39 & 0.309 \\ A3 & 5 & 2 & 1 & 2.617 & 0.582 \\ \hline \end{tabular}
\end{table}
Table 1: A judgment matrix.  
The maximum eigenvalue of the judgment matrix \(\lambda_{max}\) is 3.004. \(C.R.=0.002<0.1\) is calculated by the formula, and the consistency of the matrix can pass the test. From the normalized weights of the three sub-objectives, it can be seen that the decision makers are most interested in the safety and stability of the foundation pit structure, followed by the settlement influence coefficient, and, finally, the total cost of dewatering.  
In combination with the actual situation and relevant experience of the project, the total cost of dewatering in the sub-target layer, the settlement influence coefficient, and the safety and stability of the foundation pit structure are evaluated and scored, and the score values are shown in Table 2. Therefore, the solution with the highest score in the Pareto optimal solution set in the multi-objective optimization model is selected as the optimization decision solution.