Henri C. Jimbo
ABSTRACT
This work proposes a controlled stochastic difference equation model of scheduling, with quadratic cost criteria, for cancer chemotherapy. By reducing the problem to quadratic control optimization and introducing a random search algorithm, we seek an optimal chemotherapy schedule. Our ultimate goal is to provide more realistic solutions than previous models. To reach this goal, our model ideally kills the maximum number of cancer cells to eradicate the disease while preserving the number of normal cells. Our results show the proposed model works well for cancer chemotherapy. Our algorithm is fast and helps produce practical schedules.
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Digital Library
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- G. Ochoa, M. Villasana, and E. Burke. An evolutionary approach to cancer chemotherapy scheduling. Genetic Prog. and Evol. Machines Journal, 8(4):301-318, 2007. Google ScholarDigital Library
- Y. Sakamura. Cell concentration data, 2010. http://bsw3.naist.jp/tns/LabMembers/Research Fellow/Relative_Cell_Concentrations.pdf.Google Scholar
Index Terms
- A dynamical model of cancer chemotherapy with disturbance
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