Conventional optimization methodologies may be hindered when the automated search is stuck into local optima because of a deceptive objective function landscape. Consequently, open ended search methodologies, such as novelty search, have been proposed to tackle this issue. Overlooking the objective, while putting pressure into discovering novel solutions may lead to better solutions in practical problems. Novelty search was employed here to optimize the simulated design of a targeted drug delivery system for tumor treatment under the PhysiCell simulator. A hybrid objective equation was used containing both the actual objective of an effective tumour treatment and the novelty measure of the possible solutions. Different weights of the two components of the hybrid equation were investigated to unveil the significance of each one.

中文翻译：

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新奇搜索用于癌症治疗模拟的开发

当自动搜索由于欺骗性的目标函数景观而陷入局部最优时，传统的优化方法可能会受到阻碍。因此，已经提出了开放式搜索方法，例如新颖性搜索来解决这个问题。忽视目标，同时对发现新的解决方案施加压力，可能会在实际问题中找到更好的解决方案。此处采用新颖性搜索来优化 PhysiCell 模拟器下用于肿瘤治疗的靶向给药系统的模拟设计。使用混合目标方程，其中包含有效肿瘤治疗的实际目标和可能解决方案的新颖性度量。研究了混合方程的两个分量的不同权重，以揭示每个分量的重要性。