pymoo

SKILL.md

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), 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.

Pymoo uses a consistent minimize() function for all optimization tasks:

Single-objective: One objective to minimize/maximize Multi-objective: 2-3 conflicting objectives → Pareto front Many-objective: 4+ objectives → High-dimensional Pareto front Constrained: Objectives + inequality/equality constraints Dynamic: Time-varying objectives or constraints

Cadre d'optimisation multi-objectifs. NSGA-II, NSGA-III, MOEA/D, fronts de Pareto, gestion des contraintes, benchmarks (ZDT, DTLZ), pour les problèmes de conception technique et d'optimisation. Source : jackspace/claudeskillz.

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