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Optimal control of a cancer chemotherapy problem with different toxic elimination processes
Date Issued
2006
ISBN
0780394879
978-078039487-2
Citation
2006 IEEE Congress on Evolutionary Computation, CEC 2006, 2006, pp. 2475 - 2482, Article number 1688616
Type
Conference Paper
Abstract
In this paper, we propose two new anticancer drug scheduling models with different toxicity clearances according to kinetics of enzyme-catalyzed chemical reactions. We also present a sophisticated automating drug scheduling approach based on evolutionary computation and computer modeling. To explore multiple efficient drug scheduling policies, we use a multimodal optimization algorithm - adaptive elitist-population based genetic algorithm (AEGA) to solve the models, and discuss the situation of multiple optimal solutions under different parameter settings. The simulation results obtained by the new models match well with the clinical treatment experience, and can provide much more drug scheduling policies for a doctor to choose depending on the particular conditions of the patients. © 2006 IEEE.
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