pymoo - Solve single and multi-objective optimization problems
Use pymoo to solve constrained and unconstrained optimization problems with evolutionary algorithms, Pareto analysis, benchmarking, visualization, and decision making.
Tags
Updated: 2026-10-02Capabilities
Typical Inputs
Typical Outputs
What this skill does
- Solve optimization problems
- Find Pareto-optimal solutions
- Configure evolutionary algorithms
- Handle optimization constraints
- Run benchmark problems
- Customize genetic operators
- Visualize optimization results
- Apply multi-criteria decision making
- Support mixed variable types
Inputs
- Optimization problem
- Objective functions
- Decision variable bounds
- Optimization algorithm
- Termination criteria
- Constraint definitions
- Reference directions
- Decision preferences
Outputs
- Optimization solutions
- Objective values
- Pareto fronts
- Constraint violations
- Optimization history
- Visualization plots
- Selected preferred solutions
Requirements
- Python environment
- pymoo package
- NumPy support