Jeng-Shyang Pan

Interpretable Stochasticity for Adjustable Chance-Constrained Programming.

Uncertainty poses a significant challenge for optimization algorithms in real-world applications. As these algorithms become more sophisticated, there is an increasing need for them to produce reliable and explainable decisions under uncertain conditions. This article introduces knowledge-enabled explainable chance-con...