Andrea Fusco

Learning to Solve Two-Stage Stochastic Unit Commitment Problems with Quality Guarantees

An Input Convex Neural Network architecture is proposed to learn a convex surrogate of the second-stage value function, enabling fast first-stage optimization while preserving convexity by construction.