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Approximately solving multiobjective linear programmes in objective space and an application in radiotherapy treatment planning

机译:在目标空间中近似求解多目标线性程序及其在放射治疗计划中的应用

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In this paper, we propose a modification of Benson's algorithm for solving multiobjective linear programmes in objective space in order to approximate the true nondominated set. We first summarize Benson's original algorithm and propose some small changes to improve computational performance. We then introduce our approximation version of the algorithm, which computes an inner and an outer approximation of the nondominated set. We prove that the inner approximation provides a set of epsilon-nondominated points. This work is motivated by an application, the beam intensity optimization problem of radiotherapy treatment planning. This problem can be formulated as a multiobjective linear programme with three objectives. The constraint matrix of the problem relies on the calculation of dose deposited in tissue. Since this calculation is always imprecise solving the MOLP exactly is not necessary in practice. With our algorithm we solve the problem approximately within a specified accuracy in objective space. We present results on four clinical cancer cases that clearly illustrate the advantages of our method.
机译:在本文中,我们提出了Benson算法的一种改进,用于求解目标空间中的多目标线性程序,以便逼近真正的非支配集。我们首先总结Benson的原始算法,并提出一些小的更改以提高计算性能。然后,我们介绍算法的近似版本,该算法计算非控制集的内部和外部近似。我们证明了内逼近提供了一组ε终止点。这项工作是受放射疗法治疗计划的光束强度优化问题的应用启发的。这个问题可以表述为具有三个目标的多目标线性程序。问题的约束矩阵取决于组织中沉积剂量的计算。由于此计算始终不精确,因此在实际中完全不需要精确地求解MOLP。使用我们的算法,我们可以在目标空间中的指定精度范围内解决问题。我们提供了四个临床癌症病例的结果,清楚地说明了我们方法的优势。

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