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pymoo - Run evolutionary single- and multi-objective optimization

Define optimization problems and solve them with evolutionary algorithms, then analyze and visualize Pareto fronts and trade-offs.

Tags

Updated: 2026-10-06
optimizationevolutionary algorithmsmulti-objective optimizationPareto frontshyperparameter search

Capabilities

Define optimization problemsConfigure evolutionary algorithmsCustomize search operatorsSet termination criteria

Typical Inputs

Objective functionsConstraint functionsVariable bounds

Typical Outputs

Optimization result objectsPareto-optimal solutionsObjective values

What this skill does

  • Define optimization problems
  • Configure evolutionary algorithms
  • Customize search operators
  • Set termination criteria
  • Analyze Pareto fronts
  • Visualize optimization trade-offs
  • Compute performance indicators

Inputs

  • Objective functions
  • Constraint functions
  • Variable bounds
  • Algorithm configuration
  • Reference directions

Outputs

  • Optimization result objects
  • Pareto-optimal solutions
  • Objective values
  • Decision variable values
  • Pareto front visualizations
  • Plot files

Requirements

  • Python
  • pymoo package
  • NumPy
  • Matplotlib
  • CPU environment

Source

  • Spec: SKILL.md

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