Brownlee A, Pelikan M, McCall J & Petrovski A (2008) An application of a multivariate estimation of distribution algorithm to cancer chemotherapy. In: Keijzer M (ed.) GECCO '08 Proceedings of the 10th annual conference on Genetic and evolutionary computation. GECCO '08: 10th annual conference on Genetic and evolutionary computation, Atlanta, GA, USA, 12.07.2008-16.07.2008. New York, NY: ACM, pp. 463-464. http://dl.acm.org/citation.cfm?id=1389179; https://doi.org/10.1145/1389095.1389179
Abstract Chemotherapy treatment for cancer is a complex optimisation problem with a large number of interacting variables and constraints. A number of different heuristics have been applied to it with varying success. In this paper we expand on this by applying two estimation of distribution algorithms to the problem. One is UMDA and the other is hBOA, the first EDA using a multivariate probabilistic model to be applied to the chemotherapy problem. While instinct would lead us to predict that the more sophisticated algorithm would yield better performance on a complex problem like this, we show that it is outperformed by the algorithms using the simpler univariate model. We hypothesise that this is caused by the more sophisticated algorithm being impeded by the large number of interactions in the problem which though present, do not complicate the search for optima.