parameter-optimization - Parameter Optimization and DOE Workflow
Generate experimental designs, rank parameter sensitivity, select optimization algorithms, and fit surrogate models for simulation calibration.
Tags
Updated: 2026-09-19Capabilities
Typical Inputs
Typical Outputs
What this skill does
- Generate DOE sample plans
- Rank parameter influence
- Recommend optimization algorithms
- Fit surrogate models
Inputs
- Parameter bounds and units
- Evaluation budget limit
- Simulation noise level
- Parameter constraints
Outputs
- DOE sample plans
- Parameter sensitivity rankings
- Optimizer recommendation summaries
- Surrogate model metrics
Requirements
- Python 3.10 or higher
- Python standard library