论文标题
分布算法的多元估计应用于癌症化学疗法
An Application of a Multivariate Estimation of Distribution Algorithm to Cancer Chemotherapy
论文作者
论文摘要
对于癌症的化学治疗是一个复杂的优化问题，具有大量相互作用的变量和约束。许多不同的概率算法已应用于它，并取得了不同的成功。在本文中，我们通过将分布算法的两种估计值应用于问题来扩展。一个是UMDA，它使用类似于先前应用的EDA的单变量概率模型。另一个是HBOA，这是第一个使用多元概率模型应用于化学疗法问题的EDA。尽管本能会导致我们预测更复杂的算法将在这样的复杂问题上产生更好的性能，但我们表明，使用更简单的单变量模型，算法表现出色。我们假设这是由于问题中大量相互作用所妨碍更复杂的算法引起的，而这些算法是不需要解决方案的。
Chemotherapy treatment for cancer is a complex optimisation problem with a large number of interacting variables and constraints. A number of different probabilistic algorithms 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, which uses a univariate probabilistic model similar to previously applied EDAs. 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 are unnecessary for its solution.
