Süss Philipp, Küfer Karl-Heinz
Department of Optimization, Fraunhofer Institute for Industrial Mathematics, Fraunhofer-Platz 1, 67663 Kaiserslautern, Germany.
Linear Algebra Appl. 2008 Mar 1;428(5-6):1388-1405. doi: 10.1016/j.laa.2007.11.010.
It is commonly believed that not all degrees of freedom are needed to produce good solutions for the treatment planning problem in intensity modulated radiation therapy (IMRT). However, typical methods to exploit this fact either increase the complexity of the optimization problem or are heuristic in nature. In this work we introduce a technique based on adaptively refining variable clusters to successively attain better treatment plans. The approach creates approximate solutions based on smaller models that may come arbitrarily close to the optimal solution. Although the method is illustrated using a specific treatment planning model, the components constituting the variable clustering and the adaptive refinement are independent of the particular optimization problem.
人们普遍认为,在调强放射治疗(IMRT)中,并非所有自由度都需要用于生成治疗计划问题的良好解决方案。然而,利用这一事实的典型方法要么增加了优化问题的复杂性,要么本质上是启发式的。在这项工作中,我们引入了一种基于自适应细化变量簇的技术,以逐步获得更好的治疗计划。该方法基于较小的模型创建近似解,这些模型可以任意接近最优解。尽管该方法是使用特定的治疗计划模型来说明的,但构成变量聚类和自适应细化的组件与特定的优化问题无关。