pymoo - Run single- and multi-objective optimization in Python
Solve single- and multi-objective optimization problems with evolutionary algorithms, constraint handling, Pareto analysis, benchmarking, and visualization.
Tags
Updated: 2026-10-02Capabilities
Typical Inputs
Typical Outputs
What this skill does
- Solve optimization problems
- Find Pareto-optimal solutions
- Handle optimization constraints
- Customize genetic operators
- Benchmark optimization algorithms
- Visualize optimization results
- Select preferred solutions
Inputs
- Optimization problem definition
- Objective functions
- Constraint definitions
- Decision variable bounds
- Algorithm configuration
- Termination criteria
- Preference weights
- Visualization settings
Outputs
- Optimization results
- Pareto fronts
- Constraint violation metrics
- Algorithm history
- Visualization plots
- Selected solutions
Requirements
- Python environment
- pymoo library
- NumPy library