genetic-algorithm
CommunityEvolve optimal solutions with a flexible GA.
AuthorSPIRAL-EDWIN
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill provides a ready-to-use genetic algorithm framework for solving discrete and combinatorial optimization problems in Python, helping teams explore large search spaces without writing GA infrastructure from scratch.
Core Features & Use Cases
- Modular GA components: population handling, fitness evaluation, selection (tournament), crossover, mutation, and elitism.
- Simple extension to multi-objective optimization (e.g., NSGA-II style).
- Real-world scenario: optimize scheduling, routing, or feature selection by encoding solutions as chromosomes.
Quick Start
Run the GeneticAlgorithm example to minimize a sample objective (e.g., the Rastrigin function) using the included Python code.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: genetic-algorithm Download link: https://github.com/SPIRAL-EDWIN/MCM-ICM-2601000/archive/main.zip#genetic-algorithm Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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