## 3 Results Analysis and Discussion
### Example Verification
#### 3.1.2 Parameter Selection
[12], and the estimated values of the parameters were a = \(-\)3.963, b = \(-\)0.001, c = 0.054, d = e = 0, and f = 136.21. The MATLAB program and PSO were used to solve Models 1 and 2. The parameters of PSO were: population size m = 20; maximum evolutionary generation Gen = 100; inertia weight \(\omega\) was linearly reduced from 0.9 to 0.4; \(c_{1}\) = \(c_{2}\) = 2; \(v_{\max}\) = 0.5; and the optimization results were obtained after running for 7.5 min. [PERSON] et al. [12] calculated the optimization result in 18.2 min using a fuzzy clustering genetic algorithm. Figure 5 and Table 3 show both results. Figure 4: The relationship diagram of a, b, and Q\({}_{1}\). Figure 5: Comparison of optimization results. + Optimized results obtained by [PERSON] et al. [12], \(\bullet\) Opti-mized results obtained in this paper. Model 1 optimization obtained 23 Pareto optimal solutions; the 3D optimized results are shown in Figure 5(a). The two-dimensional diagrams of period-cost, period-quality, and cost-quality relationships are shown in Figure 5(b)-d.  
Figure 6: \(Cont\). \begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline \multicolumn{1}{c}{**Reference by [PERSON] et al. **} & \multicolumn{3}{c}{**Model**} & \multicolumn{3}{c}{**Model**} \\ \([11]\) **Optimization Results** & **Demation/Day** & **Cant/US8** & **Quality** & **1–Optional** & **Duration/Day** &  
Model 2 optimization obtained 21 Pareto optimal solutions; the 3D optimized results are shown in Figure 5(a). The two-dimensional diagrams of period-cost, period-quality, and cost-quality relationships are shown in Figure 6(b)-d.  
Figure 6: Model 1: 3D optimal results (**a**), and 2D period–cost, period–quality, and cost–quality relationships (**b**,_c**,_d**, respectively). Figure 7: _Cont_. The optimization results in this paper are consistent with the literature by [PERSON] et al. [12] in terms of Pareto solution number, duration optimization interval, and cost optimization interval, as shown in Figure 5; however, the optimization quality in this paper is relatively high. This is because the quality model adopted in literature by [PERSON] et al. [12] is \(Q=\alpha Q_{\min}+(1-\alpha)Q_{average}\), and the quality optimization interval is between the minimum quality and the average quality, that is, \(0.6193\leq Q\leq 0.8945\). After determining the relevant parameters, the optimization interval of the quality model in this paper is between [0.9233 and 0.9876], indicating that the quality level of the model optimization in this paper is relatively high. The PSO algorithm adopted in this paper has a fast convergence speed and short solving time, and can quickly find the high-quality interval and search for optimization. The results of the calculations show that the model in this paper can achieve a better balance of the three objectives of optimizing construction period, cost, and quality. As can be seen from Table 3, the optimized construction period interval in the literature by [PERSON] et al. [12] is [104; 105; 106; 107; 108; 109; 110; 111; 112; 113], the cost (USS) interval is [111; 355; 112; 113; 114; 115; 116; 117; 118; 119; 120; 121; 122; 123], and the quality interval is [0.69600-0.86234]; the optimized period interval of Model 1 is [104; 105; 106; 107; 108; 109; 110; 111; 112; 113], the cost (USS) interval is [109; 550; 106; 107; 108; 109; 110; 111; 112; 113; 114; 115; 116; 117; 118; 119; 120; 121; 123], and the quality interval is [0.9319-0.9809]. In terms of the number of Pareto solutions, the optimized interval of the construction period, and the optimized interval of cost, the optimized results of Model 1 are consistent with the literature by [PERSON] et al. [12]; however, the optimized quality level of Model 1 is higher. This is because the quality and quantity mode adopted in the literature by [PERSON] et al. [12] is \(Q=\alpha Q_{\min}+(1-\alpha)Q_{average}\), and the optimized quality interval is between the minimum quality and the average quality, i.e., \(0.6193\leq Q\leq 0.8945\).