Decision making under uncertainty: Is sensitivity analysis of any use?
Decision making under uncertainty: Is sensitivity analysis of any use?
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DOI：
10.1287/opre.48.1.20.12441
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发表时间：
2000-01-01
影响因子：
2.7
通讯作者：
Wallace, SW
中科院分区：
文献类型：
--
作者：
Wallace, SW
灵敏度分析与参数优化相结合，经常作为一种检查确定性线性规划的解是否可靠的方法——即使某些参数不完全已知，但被最佳猜测（通常是样本均值）所取代。通常认为，如果某一基最优的区域很大，则使用线性规划的解是相当安全的。如果没有，参数分析将为我们提供可测试的替代解决方案。这样，就可以利用灵敏度分析，借助于确定性工具，即参数线性规划，在不确定的情况下进行决策。我们在这篇笔记中表明，稳定性的基本思想与参数不确定的优化问题的最优性几乎没有关系。
Sensitivity analysis, combined with parametric optimization, is often presented as a way of checking if the solution of a deterministic linear program is reliable-even if some of the parameters are not fully known bur are instead replaced by a best guess, often a sample mean. It is customary to claim that if the region over which a certain basis is optimal is large, one is fairly safe by using the solution of the linear program. If not, the parametric analysis will provide us with alternative solutions that can be tested. This way, sensitivity analysis is used to facilitate decision making under uncertainty by means of a deterministic tool, namely parametric linear programming. We show in this note that this basic idea of stability has little do with optimality of an optimization problem where the parameters are uncertain.