Individual skill
pymoo
Solves single- and multi-objective optimization problems in Python with pymoo, using NSGA-II, NSGA-III, MOEA/D, SPEA2, RVEA, GA, DE and PSO. Covers custom problems (Problem, ElementwiseProblem, FunctionalProblem), constraint handling, mixed-variable problems, ZDT/DTLZ/WFG benchmarks, genetic operators, parallel evaluation, Pareto front visualization and multi-criteria decision making. Use when finding Pareto-optimal trade-offs between conflicting objectives. Use when defining a constrained or mixed-variable problem and choosing an evolutionary algorithm. Use when benchmarking algorithms on standard test problems. Use when customizing crossover or mutation operators. Use when picking one solution from a Pareto front. Not for gradient-based or convex solvers.
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SKILL.mdcore · 11,224 bytesSKILL.mdcore · 11,224 bytesSKILL.mdcore · 11,224 bytesSKILL.mdcore · 11,224 bytesSKILL.mdcore · 11,224 bytesSKILL.mdcore · 11,224 bytesreferences/algorithms.mddoc · 7,856 bytesreferences/constraints_mcdm.mddoc · 10,852 bytesreferences/operators.mddoc · 8,815 bytesreferences/parallelization.mddoc · 2,642 bytesreferences/problems.mddoc · 7,116 bytesreferences/quick_start_workflows.mddoc · 11,268 bytesreferences/visualization.mddoc · 9,229 bytesscripts/custom_problem_example.pyruns · 5,006 bytesscripts/decision_making_example.pyruns · 4,588 bytesscripts/many_objective_example.pyruns · 2,227 bytesscripts/multi_objective_example.pyruns · 1,731 bytesscripts/single_objective_example.pyruns · 1,620 bytes
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# Pymoo - Multi-Objective Optimization in Python
## Overview
Pymoo is a comprehensive Python framework for optimization with emphasis on multi-objective problems. Solve single and multi-objective optimization using state-of-the-art algorithms (NSGA-II/III, MOEA/D, SPEA2), benchmark problems (ZDT, DTLZ), customizable genetic operators, and multi-criteria decision making methods. Excels at finding trade-off solutions (Pareto fronts) for problems with conflicting objectives. Current stable release: **pymoo 0.6.1.6** (November 2025).
## Installation
```bash
uv pip install pymoo
```
For reproducible environments, pin a version: `uv pip install "pymoo==0.6.1.6"`.
