论文标题
利用差异进化来优化靶向癌症治疗
Utilizing Differential Evolution into optimizing targeted cancer treatments
论文作者
论文摘要
为了开发可发展的癌症治疗模拟器，考虑了差异进化的研究，这是由于该技术在实现问题中的高效率所致。一种基本的DE算法，即“ DE/RAND/1”来优化靶向药物输送系统的模拟设计，以在Physicell Simulator上进行肿瘤治疗。所建议的方法被证明比标准遗传算法更有效，该算法在预定义的世代数之后无法逃脱局部最小值。 DE的关键属性使其能够胜过标准EA，这一事实是，它使人口的多样性在整个世代中保持较高。这项工作将与正在进行的更广泛的适用性平台中的研究合并，该平台将设计，开发和评估针对癌症肿瘤的靶向药物输送系统。
Working towards the development of an evolvable cancer treatment simulator, the investigation of Differential Evolution was considered, motivated by the high efficiency of variations of this technique in real-valued problems. A basic DE algorithm, namely "DE/rand/1" was used to optimize the simulated design of a targeted drug delivery system for tumor treatment on PhysiCell simulator. The suggested approach proved to be more efficient than a standard genetic algorithm, which was not able to escape local minima after a predefined number of generations. The key attribute of DE that enables it to outperform standard EAs, is the fact that it keeps the diversity of the population high, throughout all the generations. This work will be incorporated with ongoing research in a more wide applicability platform that will design, develop and evaluate targeted drug delivery systems aiming cancer tumours.
