An Evolutionary Approach For Time Dependant Optimization
ICTAI '96 Proceedings of the 8th International Conference on Tools with Artificial Intelligence
Optimising cancer chemotherapy using an estimation of distribution algorithm and genetic algorithms
Proceedings of the 8th annual conference on Genetic and evolutionary computation
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This paper discusses the effects of mutation and directed intervention crossover approaches when applied to the derivation of cancer chemotherapy treatment schedules. Unlike traditional Uniform Crossover (UC), the directed intervention techniques actively choose the intervention level based on the fitness of the parents selected for crossover. This work describes how directed intervention crossover principles are more robust to mutation and lead to significant improvement over UC when applied to cancer chemotherapy treatment scheduling.