genpark-differential-evolution-vector-optimizer-skill
mcp
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Differential Evolution (DE/rand/1/bin) continuous optimizer with donor vector mutation and binomial crossover.
README.md
genpark-differential-evolution-vector-optimizer-skill
Differential Evolution (DE/rand/1/bin) continuous optimizer with donor vector mutation and binomial crossover.
Part of the GenPark AI Agent Skills Matrix. Production-ready, zero external dependencies, native Python 3.9+ standard library.
Architecture
flowchart TD
A[Initial Candidate Population] --> B[Evolutionary Selection & Variation]
B --> C[Metaheuristic Swarm Optimization]
C --> D[Optimal Global Solution]
D --> E[MCP Protocol Endpoint]
Features
- Zero Third-Party Dependencies: Pure Python standard library (
math,random). - Robust Metaheuristics: Genetic crossover/mutation, PSO swarm velocity, simulated annealing Metropolis criterion, and ACO stigmergy.
- Native MCP Protocol Support: Integrated JSON-RPC 2.0 stdio server ready for Claude Desktop, Cursor, and Windsurf.
Installation
pip install genpark-differential-evolution-vector-optimizer-skill
Or clone directly:
git clone https://github.com/alphaparkinc/genpark-differential-evolution-vector-optimizer-skill.git
cd genpark-differential-evolution-vector-optimizer-skill
python example_usage.py
Quick Start
from client import *
# Refer to example_usage.py for end-to-end execution
Model Context Protocol (MCP) Setup
Add to your claude_desktop_config.json or cursor.json:
{
"mcpServers": {
"genpark-differential-evolution-vector-optimizer-skill": {
"command": "python",
"args": ["-m", "genpark-differential-evolution-vector-optimizer-skill.mcp_server"]
}
}
}
License
MIT License. Copyright (c) 2026 AlphaPark Inc. & Alpha-Park.
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