Godley PM, Cairns D, Cowie J, McCall J & Swingler K (2008) The Effects of Mutation and Directed Intervention Crossover When Applied to Scheduling Chemotherapy. In: Keijzer M (ed.) Proceedings of the 10th annual conference on Genetic and evolutionary computation (GECCO). ACM Genetic and Evolutionary Computation Conference (GECCO) 2008, Atlanta, Georgia, 12.07.2008-16.07.2008. New York, USA: Association for Computing Machinery (ACM), pp. 1105-1106. http://portal.acm.org/toc.cfm?id=1389095&type=proceeding&coll=GUIDE&dl=GUIDE&CFID=47644191&CFTOKEN=12932833; https://doi.org/10.1145/1389095.1389300
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.
Optimal Control; Chemotherapy; Crossover; Genetic Algorithms; Genetics Mathematical models; Control theory; Genetics Computer simulation