谱风险测度及其对随机最优化的适应性
Spectral Risk Measures, With Adaptions For Stochastic Optimization
摘要：
随机最优化问题的目标往往包含期望。当风险也包含在问题描述中时，除了量化可接受的风险之外，还必须涉及风险度量，通常在目标中。为此目的，重要的是要有一个经过调整的、适应性强的和有效的评估计划，以评估现有的风险措施。在这篇文章中，不同的表示的一类重要的风险措施，谱风险措施，阐述。结果允许简洁的问题配方，他们特别适合于随机最优化问题。有效的评估算法可以建立在这些新的结果，这最终使最优化问题涉及频谱风险措施符合随机最优化。
英文摘要：
Stochastic optimization problems often involve the expectation in its objective. When risk is incorporated in the problem description as well, then risk measures have to be involved in addition to quantify the acceptable risk, often in the objective. For this purpose it is important to have an adjusted, adapted and efficient evaluation scheme for the risk measure available. In this article different representations of an important class of risk measures, the spectral risk measures, are elaborated. The results allow concise problem formulations, they are particularly adapted for stochastic optimization problems. Efficient evaluation algorithms can be built on these new results, which finally make optimization problems involving spectral risk measures eligible for stochastic optimization.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
