Liang, YongYongLiangProf. LEUNG Kwong SakMok, Tony Shu KamTony Shu KamMok2023-03-242023-03-242007Lecture 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 - 1107978-354072589-303029743http://hdl.handle.net/20.500.11861/7571In 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.enGenetic AlgorithmDrug Scheduling ModelConference Paper10.1007/978-3-540-72590-9_165