## 5 Results Analysis  
### Comparative Analysis of Algorithm Performance  
1. CPLEX. Table 11 shows that the Obis of CPLEX are the same as GA_GA in tests 1 to 6, while they are slightly lower than GA_GA in tests 7 to 12 (see test 12 in Table 11, the maximum Gap is -0.93%). Comparing columns 6 and 8 of Table 11, it is evident that, the Cpus of CPLEX are lower than GA_GA in tests 1 to 7 (with a maximum difference of about 60 s in test 6), while they exceed GA_GA in tests 8 to 12. Moreover, it fails to find the optimal solutions within the time limit in tests 10 to 12. In contrast, the maximum Cpu of GA_GA is only about 227 s in test 12, showing a significantly less increase compared to CPLEX. As the solution space expands further (as seen in Table 12, tests 13 to 22), GA_GA consistently achieves lower Obis than CPLEX within the time limit (see column 9 of Table 12). Furthermore, the Gaps between CPLEX and GA_GA show an increasing trend (see Table 12), and the maximum is about 15% (see test 22). Column 8 of Table 12 also indicates that the Cpus of CPLEX reach the time limit, whereas the maximum of GA_GA is only 962.61 s (see test 22). 2. IG+ECTT. Comparing columns 5 and 10 of Table 11, it is found that the Obis of IG+ECTT are the same as GA_GA in tests 1 to 4, while they are slightly higher than GA_GA in tests 5 to 12, with the maximum Gap being 0.88% (see test 12). Comparing columns 6, 8, and 11 of Table 11, it can be observed that the Cpus of IG+ECTT are slightly higher than CPLEX (but lower than GA_GA) only in test 1 and test 2, while in tests 3 to 12, they are significantly lower than GA_GA and CPLEX. In tests 13 to 22, the Gaps of IG+ECTT also increase (see column 12 of Table 12), but the values are significantly less than CPLEX (with a maximum of about 4.04% in test 22). However, the Cpus of IG+ECTT in Table 12 are significantly lower than GA_GA (with a maximum of only 33.76 s in test 22). 3. Other algorithms. The Gaps of IG+ECTT are lower than GA, SA, and TS (see columns 2, 3, and 4 of Table 13). The Cpus of the three algorithms are roughly the same as IG+ECTT (with a maximum of about 34 s in test 22), significantly faster than GA_GA (962 s). The Obis of SA_GA, TS_GA, GA_SA, and GA_TS (see columns 5, 6, 7, and 8 of Table 13) are lower than IG+ECTT. The Cpus of these four algorithms are comparable to GA_GA (for example, in test 22, their Cpus are about 916 s, 978 s, 923 s, and 969 s, respectively), and are all significantly higher than IG+ECTT. It can be seen that GA_GA has the best performance in reducing Obj. SA_GA, TS_GA, GA_SA, and GA_TS show clear advantages over single-layer algorithms in reducing Obj, although it does not perform as well as single-layer algorithms in terms of Cpu. However, IG+ECTT shows its advantages in reducing both Obj and Cpu. These results justify the advantages of the memetic algorithm in solving ITRTSP. Among all the algorithms mentioned above, GA_GA and IG+ECTT are more effective in solving ITRTSP. If decision-makers wish to minimize the makespan, GA_GA is preferable. If they want to minimize decision-making time, IG+ECTT may be a better choice. Additionally, although IG+ECTT saves decision-making time, the amount saved is significantly less than the makespan saved by GA_GA, SA_GA, TS_GA, GA_SA, and GA_TS. This indicates that, in the examples of