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首页> 外文期刊>IMA Journal of Management Mathematics >Development and evaluation of a matheuristic for the combined beam angle and dose distribution problem in radiotherapy planning
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Development and evaluation of a matheuristic for the combined beam angle and dose distribution problem in radiotherapy planning

机译:放射治疗计划中束角和剂量分布组合问题数学的发展和评估

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摘要

Radiotherapy planning is vital for ensuring the maximum level of effectiveness of treatment. In the planning task, there are at least two connected decision problems that can be modelled and solved using operational research techniques: determining the best position of the radiotherapy machine (beam angle problem) and the optimal dose delivered through each beam (dose distribution problem). This paper presents a mathematical optimization model for solving the combined beam angle and dose distribution problems in the presence of multiple objectives. A matheuristic based on Tabu Search (called TSrad) is developed to solve realistic large-scale instances. The performance of the proposed method is assessed on two prostate cancer instances, namely a single computed tomography (CT) slice and a set of CT slices (three-dimensional problem). For the single-slice problem, the results of TSrad are compared to the optimal solutions obtained by an exact method. Our experiments show that TSrad is able to achieve optimality for some instances. For the multi-slice problem, our experiments show that TSrad produces viable solutions that can be attained in a reasonable computational time.
机译:放射治疗计划对于确保最大程度的治疗效果至关重要。在计划任务中,至少可以使用运筹学技术来建模和解决两个相互关联的决策问题:确定放射治疗机的最佳位置(光束角度问题)和通过每个光束输送的最佳剂量(剂量分布问题) 。本文提出了一种数学优化模型,用于解决在存在多个目标的情况下组合的束角和剂量分布问题。开发了基于禁忌搜索的数学方法(称为TSrad)来解决现实的大型实例。在两个前列腺癌实例,即单个计算机断层扫描(CT)切片和一组CT切片(三维问题)上评估了所提出方法的性能。对于单切片问题,将TSrad的结果与通过精确方法获得的最优解进行比较。我们的实验表明,TSrad能够在某些情况下达到最优。对于多层问题,我们的实验表明TSrad产生了可行的解决方案,这些解决方案可以在合理的计算时间内实现。

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