Jimbo Henri Claver and Isidore Seraphin Ngongo
Cancer model, nonlinear dynamic, modelling, complex systems, medical application
Modelling and Analyzing chemotherapy treatment for cancer using mathematical framework is a complex optimization problem with huge number of constraints and variables. Previous researches have shown that several approaches can be applied to the cancer chemotherapy problem with various degree of success. In our previous work, we proposed a set of controlled stochastic differential equations to model the drug scheduling with quadratic cost criteria in cancer chemotherapy process. We developed a fast and efficient algorithm to solve such complex optimization problem. However the obtained results did not take into account the toxic side-effects of the treatment. In this work, we present an extended version of the previous model, the parsimonious tradeoff between drug dose and toxic side - effects is carefully implemented. The ultimate goal here being optimizing drug scheduling to finding appropriate treatment design from many possibilities, we applied a novel version of Adapted Genetic Algorithm to reach optimal solution to the problem. Here we will present and discuss these new findings.
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