Overview
Combinatorial optimization over outage schedules with crew routing constraints.
outageroutingcrews
Confidence
83%
Blended from documentation depth, benchmark presence, and cross-source corroboration.
Significance score: 80/100
Source metadata
- Primary source
- arXiv
- Last updated
- 2026-04-20
- Domain
- Optimization
Maturity assessment
Emerging
Assessment combines release cadence, maintainer responsiveness, and sector-specific adoption proxies.
AI-generated summary
Combinatorial optimization over outage schedules with crew routing constraints.
Utility relevance reasoning
Improves planned outage coordination and customer impact minimization across the network.
Related technologies
- LoadSense AI
Time Series Forecasting
- TransformerGrid
Optimization
- GridStability GNN
Optimization
Lineage references
Lineage Map- Upstream paper references linked in model card.
- Dataset manifests registered for reproducibility.
Source citations
- OutageGraph Optimizer README — installation, data expectations, and evaluation metrics.
- Model documentation — hyperparameters and reproducibility notes.
- Mobiloitte internal rubric MOBILOITTE-AIR-UR-02 — utility relevance scoring dimensions.
Timeline of changes
- 2026-05-02Maturity reassessed from Emerging → Growth based on adoption signals.
- 2026-04-18Utility relevance mapping refreshed for smart grid sector weighting.