# Chemotherapy Regimen Optimization Using a Two-Archive Multi-Objective Squirrel Search Algorithm
## 4 Experimental Setup and Results Analysis
### Results and Analysis
#### 4.4.5 Robustness Analysis
It can be observed that, during aggressive chemotherapy, although the +10% parameter regimen shows a smaller decrease in tumor cell count in the early stages of treatment, ultimately the chemotherapy regimens under all three parameter conditions achieve similar reductions in tumor cells, with remaining tumor cell proportions of 4.30%, 4.96%, and 4.19%, respectively, mirroring the characteristics of the Pareto front curves shown in Figure 11. The corresponding drug concentrations for all three chemotherapy regimens remain relatively high, with minimal differences in cumulative bone marrow cell damage and minimum bone marrow cell values. It is worth noting that the number of remained cells of the +10% parameters scenario is significantly higher than in the other two scenarios. In terms of clinical significance, +10% and -10% scenarios denote larger and smaller initial tumor sizes before any treatment is applied, and the algorithm TA-MOSSA optimized chemotherapy treatment accordingly. Furthermore, the +10% scenario tumor also grows faster than others, indicating a less favorable prognosis for patients under these conditions. Therefore, the larger number of remaining tumor cells observed in the +10% parameter scenario indicates that, even when feasible treatment is applied, larger tumor and higher growth rates still result in more remaining cells. However, it is obvious that the difference over the number of remained tumor cells among these parameter scenarios is quite slight, indicating  
Figure 14: Long-term dynamics of tumor cell and bone marrow cell population after aggressive chemotherapy treatment. Figure 15: Long-term dynamics of tumor cell and bone marrow cell population after mild chemotherapy treatment. the algorithm's ability and robustness over varying parameters to optimize treatment plans based on varying patient parameters under the situation of non-cycle-specific and cycle-specific combination chemotherapy, efficiently addressing different tumor sizes and conditions; it may also be more efficient for larger tumor situation. Drawing from Figure 14, after aggressive treatment, the tumor cell levels are quite low and remain low for a long time without further doses. On the other hand, bone marrow cells quickly rebound to levels near the carrying capacity. During mild chemotherapy, the trends in tumor cell and bone marrow cell populations generated by the chemotherapy regimens under different parameter conditions exhibit similar patterns; however, there are slight differences in the endpoints of the tumor cell count change curves, with the maximum difference of approximately \(0.5\times 10^{10}\), indicating a close level of similarity. Regarding the bone marrow cell population, following the initial dose of the \(-10\%\) parameter regimen, there is a sharp drop observed in its bone marrow cell population, distinguishing it from the other regimens. However, from day 20 of treatment until the end of the treatment period, all three trends stabilize at similar levels. Additionally, cumulative bone marrow cell damage and average values remain consistent, while drug concentrations show minor fluctuations within a small range, with the maximum difference not exceeding 0.03. Referring to Figure 15, in the case of mild treatment, the tumor cell levels rise faster than in the aggressive treatment scenario within a period after chemotherapy is completed. Meanwhile, bone marrow cells gradually return to levels near the carrying capacity, comparatively. Based on the results of the robustness experiment described above, it can be concluded that the proposed TA-MOSSA can provide effective chemotherapy regimens for patients with different conditions, demonstrating robustness and reliability in both aggressive and mild chemotherapy scenarios.