Sensitivity analysis is an important component of simulation-based decision support because it helps analysts determine which inputs most strongly influence model outcomes under uncertainty. This paper organizes the broad sensitivity analysis literature into a coherent framework for use in complex simulation settings, with particular attention to military applications. We review major classes of methods, including local and global approaches, variance-based techniques, screening methods, derivative-based methods, and uncertainty quantification tools, and relate them to common analytical objectives such as factor prioritization, factor fixing, variance reduction, and factor mapping. The paper also discusses sensitivity auditing as a complementary perspective that emphasizes transparency, assumption tracking, and responsible use of models in decision-relevant settings.

翻译：灵敏度分析是基于仿真的决策支持的重要组成部分，因为它有助于分析人员在不确定性条件下确定哪些输入对模型输出结果影响最为显著。本文在复杂仿真应用背景下，将广泛的灵敏度分析文献整合为一个连贯的框架，并特别关注军事应用场景。我们综述了主要的方法类别，包括局部与全局方法、基于方差的技术、筛选方法、基于导数的方法以及不确定性量化工具，并将它们与常见的分析目标（如因子优先排序、因子固定、方差缩减和因子映射）相关联。本文还讨论了作为补充视角的灵敏度审计，该方法强调在决策相关背景下模型的透明度、假设追踪以及负责任使用。