Scenario Selection

Scenario selection focuses on efficiently identifying and prioritizing the most relevant scenarios from a potentially vast space of possibilities for simulation-based optimization and testing. Current research emphasizes developing algorithms and models, such as those incorporating Transformer networks, semi-smooth Newton methods, and functional depth metrics, to improve the speed and accuracy of scenario selection across diverse applications. This work is crucial for addressing computational challenges in areas like automated vehicle testing, power grid planning, and financial risk management, enabling more robust and efficient decision-making processes.