Fast Drug Scheduling Optimization Approach for Cancer Chemotherapy

Authors:
Yong Liang;Kwong-Sak Leung;Tony Shu Mok
Affiliations:
Department of Computer Science, Shantou University, China;Department of Computer Science & Engineering, The Chinese University of Hong Kong, HK;Department of Clinical Oncology, The Chinese University of Hong Kong, HK
Venue:
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007
Year:
2007

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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.