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Dual therapy of cancer using optimal control supported by swarm intelligence.
- Source :
-
Bio-Medical Materials & Engineering . 2024, Vol. 35 Issue 3, p249-264. 16p. - Publication Year :
- 2024
-
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. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09592989
- Volume :
- 35
- Issue :
- 3
- Database :
- Academic Search Index
- Journal :
- Bio-Medical Materials & Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 177634896
- Full Text :
- https://doi.org/10.3233/BME-230150