Description
pymoo is an agent skill for solving and validating single-, multi- and many-objective optimisation problems with the pymoo Python framework. It covers algorithms such as NSGA-II, NSGA-III, MOEA/D and SPEA2, benchmark problems such as ZDT and DTLZ, constraints, Pareto front approximations, customisable genetic operators and multi-criteria decision-making methods. It is most useful when objectives conflict and you want the trade-off solutions, which form a Pareto front. The skill targets stable pymoo 0.6.2, reviewed on 1 October 2026 against the current official documentation and native test runs. Installation is through uv, and the skill recommends pinning the version for reproducible environments. The released 0.6.2 wheel requires NumPy, SciPy, moocore, autograd, cma, matplotlib, alive_progress and Deprecated. NumPy 2 is supported. Joblib, Optuna and dill are separate dependencies for the recipes that use them. The skill notes that the released package metadata governs installation where the prose documentation differs. Use it when you are optimising designs or parameters against several goals and need to see the trade-offs.…
Highlights
- NSGA-II, NSGA-III, MOEA/D and SPEA2
- Single, multi and many-objective problems
- ZDT and DTLZ benchmark problems
- Constraints and Pareto front approximations
- Targets pymoo 0.6.2
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pymoo FAQ
What does pymoo solve?
Single, multi and many-objective optimisation, with algorithms such as NSGA-II, NSGA-III and MOEA/D.
When is it useful?
When objectives conflict and you want the trade-off solutions that form a Pareto front.
Which version is covered?
Stable pymoo 0.6.2, reviewed on 1 October 2026.
Which NumPy version works?
NumPy 2.x is supported, according to the skill.
How do I install it?
Run npx skills add https://github.com/k-dense-ai/scientific-agent-skills --skill pymoo.
Is it checked for security?
Its security audits show passes from Gen Agent Trust Hub, Socket and Snyk.
What are the best pymoo alternatives?
Popular alternatives to pymoo include python-performance-optimization, benchmark-optimization-loop and cost-aware-llm-pipeline. See all pymoo alternatives