Porcupy: Crested Porcupine Optimizer

A Python implementation of the Crested Porcupine Optimizer (CPO) algorithm, featuring GPU acceleration and comprehensive visualization tools.

Getting Started

• Quick Start Guide
  • Your First Optimization
  • Understanding the Output
  • Visualizing the Results
  • Using GPU Acceleration
  • Next Steps
• Installation Guide
  • Prerequisites
  • Installing Porcupy
  • Verifying Installation
  • Troubleshooting
• Configuration Guide
  • Basic Configuration
  • Advanced Configuration
  • GPU Configuration
  • Environment Variables
  • Performance Tuning
  • Configuration Examples

Examples

• Basic Optimization Examples
  • Table of Contents
  • Minimizing a Simple Function
  • Optimizing with Constraints
  • Using Different Benchmark Functions
  • Visualizing the Optimization Process
  • Saving and Loading Results
  • Real-world Example: Hyperparameter Tuning
  • Tips for Better Performance
  • Next Steps
• Advanced Optimization Examples
  • Table of Contents
  • Multi-Objective Optimization
  • Dynamic Optimization
  • Hybrid Optimization
  • Surrogate-Assisted Optimization
  • Distributed Optimization
  • Custom Optimization Loop
  • Advanced Constraint Handling
  • Performance Tips for Advanced Usage
• Real-World Applications
  • Table of Contents
  • Hyperparameter Tuning for Machine Learning
  • Neural Network Architecture Search
  • Portfolio Optimization
  • Engineering Design Optimization
  • Supply Chain Optimization
  • Energy System Optimization
  • Tips for Real-World Applications

API Reference

• Porcupy API Reference
  • Core Classes
  • Backend Components
  • Population Management
  • Visualization
  • Benchmark Functions
  • Legacy API
  • Utility Modules
• API Reference
  • porcupy

Indices and tables

• Index

• Module Index

• Search Page