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Fast drug scheduling optimization approach for cancer chemotherapy
Date Issued
2007
Publisher
Springer Verlag
ISBN
978-354072589-3
ISSN
03029743
Citation
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2007, vol. 4490 LNCS, Issue PART 4, Pages 1099 - 1107
Type
Conference Paper
Abstract
In this paper, we propose a novel fast evolutionary algorithm - cycle-wise genetic algorithm (CWGA) based on the theoretical analyses of a drug scheduling mathematical model for cancer chemotherapy. CWGA is more efficient than other existing algorithms to solve the drug scheduling optimization problem. Moreover, its simulation results 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. CWGA also can be widely used to solve other kinds of the real dynamic systems. © Springer-Verlag Berlin Heidelberg 2007.
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