arxiv
PublishedApril 16, 2026 at 4:00 AM
▲bullish
Neural Two-Stage Stochastic Optimization for Solving Unit Commitment Problem
Publisher summary· verbatim
arXiv:2507.09503v4 Announce Type: replace-cross Abstract: This paper proposes a neural stochastic optimization method for efficiently solving the two-stage stochastic unit commitment (2S-SUC) problem under high-dimensional uncertainty scenarios. The proposed method approximates the second-stage reco
Stay posted· Newsletter
Three short emails a week: Monday, Wednesday and Friday. Top movers, new models and the most-referenced story.
Your email is used only to send The Bubble Brief. Privacy policy
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivNewsBench: Expert-Grounded Evaluation of Epistemic Quality in AI News Reporting5harxivAdaPRA: Process Reward Agents with Adaptive Rubrics for Data Science5harxivScoped Semantic Invariance as a Foundation for LLM Reliability5harxivAn actively trained neural operator for near-explicit atmospheric chemistry5hThe Bubble Brief
MON · WED · FRIRead optimization insights every Monday, Wednesday and Friday — top movers, new models, story of the week.
Your email is used only to send The Bubble Brief. Privacy policy
Originally published on arxiv ↗