A robust-CVaR optimization approach with application to breast cancer therapy
A robust-CVaR optimization approach with application to breast cancer therapy
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DOI：
10.1016/j.ejor.2014.04.038
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发表时间：
2014-11-01
影响因子：
6.4
通讯作者：
Purdie, Thomas G.
中科院分区：
文献类型：
--
作者：
Chan, Timothy C. Y.;Mahmoudzadeh, Houra;Purdie, Thomas G.
我们提出了一个框架，以优化条件风险价值（CVaR）的损失分布下的不确定性。我们的模型假设损失分布依赖于某些系统的状态，并且在每个状态下花费的时间比例是不确定的。我们开发和比较两个强大的CVaR公式，考虑到这种类型的不确定性。我们激励和展示我们的方法，使用放射治疗乳腺癌的治疗计划，其中的不确定性是在患者的呼吸运动和系统的状态是患者的呼吸周期的阶段。我们使用CVaR表示的剂量分布的尾巴在身体中的点，并考虑到患者的呼吸模式，影响整体剂量分布的不确定性。(C)2014爱思唯尔有限公司版权所有。
We present a framework to optimize the conditional value-at-risk (CVaR) of a loss distribution under uncertainty. Our model assumes that the loss distribution is dependent on the state of some system and the fraction of time spent in each state is uncertain. We develop and compare two robust-CVaR formulations that take into account this type of uncertainty. We motivate and demonstrate our approach using radiation therapy treatment planning of breast cancer, where the uncertainty is in the patient's breathing motion and the states of the system are the phases of the patient's breathing cycle. We use a CVaR representation of the tails of the dose distribution to the points in the body and account for uncertainty in the patient's breathing pattern that affects the overall dose distribution. (C) 2014 Elsevier B.V. All rights reserved.