AI-Driven, Timing-Aware Power Optimization
The framework uses an AI-driven system to decide which power recovery edits and subsequent repairs to attempt during post-route optimization. It employs a learned policy, based on ensemble models, to rank these actions using uncertainty-aware scores. This decision process is governed by a strict contract that prioritizes preserving baseline constraints while staying within a budget tied to the measured power savings.