What-if analysis is a systematic approach used to evaluate the effects of varying inputs or assumptions in a model to determine potential outcomes. This technique allows decision-makers to explore different scenarios and their impacts on results, helping them understand risks and make informed choices. In the context of two-stage stochastic programs, it plays a crucial role in assessing how changes in uncertainty or parameters can affect optimal decisions and overall performance.
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