00000cab a22000003a 4500 UP-99796217609533001 Buklod 20231007234405.0 m |o d | ta 101110s xx d | ||r ||||| || DENGII eng Yong Liang A novel evolutionary drug scheduling model in cancer chemotherapy. pp. 237-245 In this paper, we introduce a modified optimal control model of drug scheduling in cancer chemotherapy and a new adaptive elitist-population-based genetic algorithm (AEGA) to solve it. Working closely with an oncologist, we first modify the existing model, because its equation for the cumulative drug toxicity is inconsistent with medical knowledge and clinical experience. To explore multiple efficient drug scheduling policies, we propose a novel variable representation-a cycle-wise representation, and modify the elitist genetic search operators in the AEGA. The simulation results obtained by the modified model match well with the clinical treatment experiences, and can provide multiple efficient solutions for oncologists to consider. Moreover, it has been shown that the evolutionary drug scheduling approach is simple, and capable of solving complex cancer chemotherapy problems by adapting multimodal versions of evolutionary algorithms Adaptive elitist-population-based genetic algorithm. Cancer chemotherapy. Evolutionary algorithm. Evolutionary drug scheduling model. Optimal control model. IEEE Transactions on information technology in biomedicine 10, 2 (2006). FO UPD DENG-II Article