A new conformal framework learns polyhedral uncertainty sets tailored to robust optimization objectives, minimizing decision loss while preserving coverage via calibration and independent re-calibration.
Enhancing electricity- system resilience with adaptive robust optimization and conformal uncertainty characterization
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A data-driven tri-level adaptive robust optimization model with a scalable column-and-constraint generation algorithm jointly optimizes long-term grid configuration and short-term operational mitigation for wildfire ignition uncertainty, validated on synthetic data and a large utility distribution系统
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Learning Polyhedral Conformal Sets for Robust Optimization
A new conformal framework learns polyhedral uncertainty sets tailored to robust optimization objectives, minimizing decision loss while preserving coverage via calibration and independent re-calibration.
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Large-Scale Resilience Planning for Wildfire-Prone Electricity-System via Adaptive Robust Optimization
A data-driven tri-level adaptive robust optimization model with a scalable column-and-constraint generation algorithm jointly optimizes long-term grid configuration and short-term operational mitigation for wildfire ignition uncertainty, validated on synthetic data and a large utility distribution系统