TJ914 : Proposing the multi-objective optimization algorithm MOEO for mixed chemo-immunotherapy of cancer
Thesis > Central Library of Shahrood University > Mechanical Engineering > MSc > 2022
Authors:
Komeil Nozad [Author], Seyyed Mojtaba Varedi-Koulaei[Supervisor], Mostafa Nazari[Supervisor]
Abstarct: Mathematical modeling of biological systems is one of the most desirable and optimal methods to study the behavior of these phenomena. Also, the development of mathematical models for simulating, controlling and predicting phenomena has always been important. The issue of cancer treatment is one of the most important issues in the optimization field, which has been the focus of many scientists and researchers in the field of biological systems and mathematics. The problem of cancer treatment is raised as an optimal control problem with the aim of reducing the concentration of cancer cells in a period of time along with reducing the drug concentration in the treatment. One of the efficient methods in the solving optimization problems is the use of mexta-heuristic algorithms. According to this issue, the present research has been carried out with the aim of obtaining an optimal drug administration protocol by considering the minimization of the concentration of cancer cells and the minimization of the drug concentration simultaneously. For this purpose, an efficient multi-objective algorithm called MOEO was introduced and used to solve the optimization problem. In this research, two well-known models of cancer modeling are selected, and a comparison is made between the results obtained with this algorithm and several famous multi-objective optimization algorithms for both models. The results obtained for the first model show that the new proposed MOEO algorithm has obtained similar answers and, in some cases, far better answers than the famous multi-objective optimization algorithms such as NSGA-II, MODE and MOPSO. In the first patient to the third patient of this model respectively and only by using 8, 20 and 7 doses of chemotherapy drugs, complete treatment was performed for the patients and the number of cancer cells in the shortest period of time for all three patients was It reaches zero. In the following, the applied results of the answers obtained from the optimizer algorithm on the second model, which includes two patients, indicate complete cancer treatment in 19 days for patient 9 and 15 days for patient 10. Meanwhile, the amount of chemotherapy drug for patient 9 is 0.4384, which is close to zero. For patient 10, the amount of chemotherapy drug changed from 27 in the last study to 5.8404 in the current study, showing a decrease of 21.1596 units. This result is one of the most important achievements of the current research.
Keywords:
#Cancer Treatment #Chemotherapy #Immunotherapy #Cancer Modeling #Multi-Objective Optimization #mextaheuristic algorithms Keeping place: Central Library of Shahrood University
Visitor: