Tan, Poh Ling and Kanesan, Jeevan and Chuah, Joon Huang and Badruddin, Irfan Anjum and Abdellatif, Abdallah and Kamangar, Sarfaraz and Hussien, Mohamed and Baig, Maughal Ahmed Ali and Ahammad, N. Ameer (2024) Dual therapy of cancer using optimal control supported by swarm intelligence. Bio-Medical Materials and Engineering, 35 (3). pp. 249-264. ISSN 0959-2989, DOI https://doi.org/10.3233/BME-230150.
Full text not available from this repository.Abstract
BACKGROUND: The scientific revolution in the treatment of many illnesses has been significantly aided by stem cells. This paper presents an optimal control on a mathematical model of chemotherapy and stem cell therapy for cancer treatment. OBJECTIVE: To develop effective hybrid techniques that combine the optimal control theory (OCT) with the evolutionary algorithm and multi-objective swarm algorithm. The developed technique is aimed to reduce the number of cancerous cells while utilizing the minimum necessary chemotherapy medications and minimizing toxicity to protect patients' health. METHODS: Two hybrid techniques are proposed in this paper. Both techniques combined OCT with the evolutionary algorithm and multi-objective swarm algorithm which included MOEA/D, MOPSO, SPEA II and PESA II. This study evaluates the performance of two hybrid techniques in terms of reducing cancer cells and drug concentrations, as well as computational time consumption. RESULTS: In both techniques, MOEA/ D emerges as the most effective algorithm due to its superior capability in minimizing tumour size and cancer drug concentration. CONCLUSION: This study highlights the importance of integrating OCT and evolutionary algorithms as a robust approach for optimizing cancer chemotherapy treatment.
| Item Type: | Article |
|---|---|
| Funders: | UM International Collaboration (ST023-2022), King Khalid University King Saud University (RGP.2/201/44) |
| Uncontrolled Keywords: | Hybrid optimal control; particle swarm optimization; evolutionary algorithms; constrained optimization; multiobjective optimization |
| Subjects: | T Technology > TJ Mechanical engineering and machinery T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Engineering > Department of Electrical Engineering |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 14 Nov 2024 02:44 |
| Last Modified: | 14 Nov 2024 02:44 |
| URI: | http://eprints.um.edu.my/id/eprint/45897 |
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