school
Macau Periodical Index (澳門期刊論文索引)
- Author
- Liang, Yong; Leung, Kwong Sak; Mok, Shu Kam
- Title
- A novel drug scheduling optimization model with drug-resistant tumor cell growth for cancer chemotherapy
- Journal Name
- 澳門科技大學學報
- Pub. Info
- Jun. 2008, Vol.2, No.1, pp. 11-22
- Keyword
- Drug scheduling optimization problem；Multimodal optimization；Genetic algorithm
- Abstract
- Abstract : This paper presents a novel drug scheduling optimization model with drug-resistant tumor cell growth for cancer chemotherapy and its corresponding renewed multimodal optimization genetic algorithm. Working closely with an oncologist, we firstly propose the new model, because the existing model for drug resistant tumor cell growth is not consistent with the clinical experience and the medicinal knowledge. For exploring multiple efficient drug scheduling policies, we improve our proposed adaptive elitist population-based genetic algorithm (AEGA) to solve it. The results obtained by the new model match well with the general treatment practice (the repeated drug schedule for cancer chemotherapy), and can provide much more realistic solutions than that by the previous model. Paragraph Headings: 1. Introduction 2. Problem statement 3. The new model including drug resistance by the cancer cells 4. Optimization of the drug scheduling model via AEGA 4.1. Variable representation 4.2. Elitist crossover operator for the cycle-wise variable representation 4.3. Elitist mutation operator for the cycle-wise variable representation 4.4. Population control constraints 4.5. AEGA for the new drug scheduling model 5. Experimental results under the new model 6. Discussion on the new model 7. Conclusion Tables: 1. The parameters of the cancer chemotherapy model 2. The multi-point crossover operator for the cycle-wise variable representation 3. The one-point mutation operator for the cycle-wise variable representation 4. The most efficient drug scheduling policies obtained by our new model Figures: 1. The best-known solutions obtained by the Martin's drug scheduling model 2. General physiological toxicokinetic model 3. The fifth efficient drug scheduling policy under our new model 4. The sixth efficient drug scheduling policy under our new model