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math.OC2026
Self-Supervised Tuning of Low-Fidelity Optimization Models via High-Fidelity Feedback
Gonzalo E. Constante-Flores, André H. Quisaguano-Paredes, Asha Ramanujam +2
Low-fidelity (LF) optimization models are widely used in large-scale operations because they can be solved efficiently and reliably, but they often exhibit systematic errors relati…
math.OC2026
Self-Supervised Learning of Parametric Approximation for Security-Constrained DC-OPF
Anderson Anrrango, André Quisaguano, Gonzalo E. Constante-Flores +1
This paper introduces a self-supervised learning framework for approximating the Security-Constrained DC Optimal Power Flow (SC-DCOPF) problem using a parametric linear model. The…