feat: Add Adaptive Method Selector for intelligent optimization strategy
The AMS analyzes optimization problems and recommends the best method:
- ProblemProfiler: Static analysis of config (dimensions, objectives, constraints)
- EarlyMetricsCollector: Dynamic analysis from FEA trials (smoothness, correlations)
- AdaptiveMethodSelector: Rule-based scoring for method recommendations
- RuntimeAdvisor: Mid-run monitoring for method pivots
Key features:
- Analyzes problem characteristics (n_variables, n_objectives, constraints)
- Computes response smoothness and variable sensitivity from trial data
- Recommends TURBO, HYBRID_LOOP, PURE_FEA, or GNN_FIELD
- Provides confidence scores and suggested parameters
- CLI: python -m optimization_engine.method_selector <config> [db]
Documentation:
- Add SYS_15_METHOD_SELECTOR.md protocol
- Update CLAUDE.md with new system protocol reference
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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