Samy, Prakas Gopal and Kanesan, Jeevan and Tiu, Zian Cheak (2023) Optimization of Chemotherapy Using Hybrid Optimal Control and Swarm Intelligence. IEEE Access, 11. pp. 28873-28886. ISSN 2169-3536, DOI https://doi.org/10.1109/ACCESS.2023.3254210.
Full text not available from this repository.Abstract
This study aimed to minimize the tumor cell population using minimal medicine for chemotherapy treatment, while maintaining the effector-immune cell population at a healthy threshold. Therefore, a mathematical model was developed in the form of ordinary differential equations (ODE), and the solution to the Multi-Objective Optimal Control Problem (MOOCP) was obtained using Multi-Objective Optimization algorithms. In this study, the interaction of the tumor cell and effector cell populations with chemotherapy was investigated using Pure MOOCP and Hybrid MOOCP methods. The handling of constraints and the Pontryagin Maximum Principle (PMP) differ among these methods. Swarm Intelligence (SI) and Evolutionary Algorithms (EA) were used to process the results of these methods. The numerical outcomes of SI and EA are displayed via the Pareto Optimal Front. In addition, the solutions from these algorithms were further analyzed using the Hypervolume Indicator. The findings of this study demonstrate that the Hybrid Method outperforms Pure MOOCP via Multi-Objective Differential Evolution (MODE). MODE produces a point on the Pareto Optimal Front with a minimal distance to the origin, where the distance represents the best solution.
| Item Type: | Article |
|---|---|
| Funders: | UNSPECIFIED |
| Uncontrolled Keywords: | Mathematical models; Tumors; Optimal control; Chemotherapy; cancer; Optimization; drugs; Particle swarm optimization; Evolutionary algorithms; Multi-objective optimal control problem; Pontryagin maximum principle; swarm intelligence; evolutionary algorithms |
| Subjects: | T Technology > T Technology (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Engineering Faculty of Engineering > Department of Electrical Engineering |
| Depositing User: | Ms Zaharah Ramly |
| Date Deposited: | 01 Nov 2024 08:04 |
| Last Modified: | 01 Nov 2024 08:04 |
| URI: | http://eprints.um.edu.my/id/eprint/39107 |
Actions (login required)
 |
View Item |
