## 5 Numerical Experiment
### Scenario Setting
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**OD Pair** & **Path Number** & **Alternative Transport Plan** & **Arvival Time of Trains from the Departure Station** & **Transportation Time/min** \\ \hline \multirow{8}{*}{Anshan–Harbin} & 1 & Anshan West Station G729 & 19:19 & 177 \\  & 2 & Anshan West Station G767 & 18:05 & 194 \\  & 3 & Anshan West Station G717 & 13:32 & 198 \\  & 4 & Anshan West Station G771 & 8:11 & 200 \\ \cline{1-1}  & 5 & Anshan West Station DJXX1 & 6:10 & 220 \\ \cline{1-1}  & 6 & Shenyang North Station G47 & 8:11 & 235 \\ \cline{1-1}  & 7 & Shenyang North Station & 17:27 & 249 \\ \cline{1-1}  & 8 & Shenyang North Station G767 & 18:05 & 251 \\ \cline{1-1}  & 8 & Shenyang North Station G729 & & \\ \cline{1-1}  & 9 & Shenyang North Station G941 Harbin West Station & 19:19 & 257 \\ \cline{1-1}  & 10 & Shenyang North Station G717 & & \\ \cline{1-1}  & 10 & Shenyang North Station G2633 Harbin West Station & 13:32 & 279 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Anshan–Harbin alternative transport plan. Some basic parameters for the model are set and shown in Table 6. \begin{table}
\begin{tabular}{c c c} \hline
**Parameter** & **Description** & **Value** \\ \hline \(s^{p}\) & Different categories of express delivery goods’ pricing and revenue parameters & (0.03, 0.025, 0.02) \\ \(c_{tr}^{e,r}\) & Express delivery goods’ freight parameters & (0.006, 0.01) \\ \(c_{l}\) & Express delivery goods’ loading and unloading cost parameters & 0.3 \\ \(c_{sto}\) & Express delivery goods’ transfer cost parameters & 0.5 \\ \(\theta^{p}\) & Critical coefficient of delay penalty cost for different categories of express & (1.2, 1.0, 0.8) \\ \(a_{e,t}^{p}\) & Promised delivery time limit for cargo flow \(f_{e,t}^{p}\) & (12, 24, 36) * 60 \\ \(t_{p}^{\pi}\) & Maximum acceptable delay time for different categories of express & (2, 3, 4) * 60 \\ \(n^{a}\) & Express loading capacity parameters for trains in different modes & (10,000, 1000) \\ \(ef\) & Loading and unloading capacity parameters for train stations & 320 \\ \(N\) & Population size & 100 \\ \((k1,k3)\) & Parameters of crossover probability & (0.7, 0.75) \\ \((k2,k4)\) & Parameters of mutation probability & (0.2, 0.2) \\ \(X\) & Maximum number of iterations & 100 \\ \(d^{e}\) & Distance between OD pair \(e\) & See Table 2 \\ \(f_{e,t}^{p}\) & Freight traffic volume of express product \(p\) with shipping time \(t\) between & See Table 3 \\ \(\text{OD pair }e\) & & \\ \hline \end{tabular}
\end{table} 
Table 6: Model parameter values. Figure 6: Alternative set of high-speed rail express transport plans from Anshan to Harbin. Figure 7: Alternative set of high-speed rail express transport plans from Dalian to Harbin. The objective function is 42,948 when the population size is 100, 44,172 when the population size is 130, and 44,326 when the population size is 160. The best choice in terms of objective function merit was 160. However, the most suitable population size is 100. When the number of iterations is 100, the crossover probability is (1,1) and the mutation probability is (0.2,0.2). The same analysis method is used to analyze the data in Table 7, which show that the most suitable population size is 100 when the number of iterations is 100, the crossover probability is (1,1) and the mutation probability is (0.3,0.3), and that the most suitable population size is 100 when the number of iterations is 100, the crossover probability is (1,1), and the mutation probability is (0.5,0.5). From the perspective of the objective function, the population size of 100 is the largest objective function value; from the perspective of the running time of the program, the running time of Experiment 1 is between that of Experiment 2 and Experiment 3, so a population size of 100 and a variance probability of (0.2,0.2) is the best combination of parameters for the current experimental environment. The cross-sectional probabilities are adjusted in two stages: fixing k1 and adjusting k3; and adjusting k1 on the basis of k3.