Fast drug scheduling optimization approach for cancer chemotherapy
Refereed conference paper presented and published in conference proceedings


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AbstractIn 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.
All Author(s) ListLiang Y., Leung K.-S., Mok T.S.K.
Name of Conference7th International Conference on Computational Science, ICCS 2007
Start Date of Conference27/05/2007
End Date of Conference30/05/2007
Place of ConferenceBeijing
Country/Region of ConferenceChina
Detailed descriptionorganized by ICCS ,
Year2007
Month12
Day1
Volume Number4490 LNCS
Issue NumberPART 4
PublisherSpringer Verlag
Place of PublicationGermany
Pages1099 - 1107
ISBN9783540725893
ISSN0302-9743
LanguagesEnglish-United Kingdom
KeywordsDrug scheduling model, Genetic algorithm

Last updated on 2020-05-09 at 23:03