oopoa 0.2

OOPOA CLI Tool (Object-Oriented Programming Optimization Algorithm)

🧠 OOPOA CLI – Object-Oriented Programming Optimization Algorithm

OOPOA CLI is a research-grade command-line tool that fully implements the Object-Oriented Programming Optimization Algorithm (OOPOA) — a novel metaheuristic introduced in 2024.

Table of Conetent

• 🧠 OOPOA CLI – Object-Oriented Programming Optimization Algorithm
  • Table of Conetent
  • Functionalities Overview:
  • 📖 Original Paper Reference
  • 🚀 Features
  • 📦 Installation
  • 📁 Project Structure
  • 🧪 Examples
  • 🧠 Mathematical Basis
  • 🧾 Citation & Credits
  • 🛣 Roadmap
  • 💬 Feedback & Contributions
  • 📄 License

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Functionalities Overview:

Multi-Graph	Custom Plot
Custom Functions	Default Functions
Custom Population	Custom Benchmark

The original paper presented only high-level pseudocode and performance graphs. This CLI bridges that gap by offering:

• 📌 A complete implementation of the algorithm logic
• 🔬 Reproducible benchmarking across standard test functions
• 📊 Exportable logs and convergence plots
• 🧠 Clear math documentation and customizable settings

Ideal for students, researchers, and developers working in optimization and metaheuristics.

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📖 Original Paper Reference

Hosny, K.M., Khalid, A.M., Said, W., Elmezain, M., & Mirjalili, S. (2024).
A novel metaheuristic based on object-oriented programming concepts for engineering optimization.
Alexandria Engineering Journal. DOI: 10.1016/j.aej.2024.04.060

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🚀 Features

• 🔧 Run OOPOA on standard benchmark functions (Sphere, Ackley, Rastrigin, etc.)
• 📉 Plot convergence graphs and export them to .png
• 🧮 Log results per iteration in .csv for reproducible analysis
• 🖋 Customizable: population size, mutation rate, bounds, and more
• 🧱 Modular codebase for easy extension (custom functions, batch runs, etc.)

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📦 Installation

git clone https://github.com/LA-10/oop-optimizer.git
cd oopoa-cli
pip install -e .

Then run the tool:

oopoa --help

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📁 Project Structure

oopoa-cli/
├── cli/               # Command-line interface (Click)
├── core/              # Algorithm logic and solution objects
├── benchmark/         # Standard benchmark functions
├── plots/             # Plotting utilities
├── examples/          # CLI usage examples
├── results/           # Auto-generated fitness logs and plots
├── docs/              # Math notes, roadmap, and usage docs
└── tests/             # (planned) unit tests

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🧪 Examples

    examples/run_sphere.sh

More CLI examples can be found in the examples/ folder.

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🧠 Mathematical Basis

OOPOA simulates OOP principles during optimization:

Status	Meaning
0 (public)	Use individual’s own value
1 (protected)	Inherit value from another solution
2 (private)	Generate new random value

See docs/math.md for full derivation and update rules.

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🧾 Citation & Credits

This implementation is based on:

Hosny, K.M., Khalid, A.M., Said, W., Elmezain, M., & Mirjalili, S. (2024).
A novel metaheuristic based on object-oriented programming concepts for engineering optimization.
Alexandria Engineering Journal. DOI

Please cite the paper if this tool supports your work. This implementation was independently developed based on the pseudocode and descriptions in the paper.

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🛣 Roadmap

Planned additions (see docs/roadmap.md):

• 📊 Plotting multiple runs
• 🧾 Config-based runs (.json, .yaml)
• 📈 Summary tables for performance across runs
• 🔁 Comparison with other metaheuristics

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💬 Feedback & Contributions

If you've used this tool, found a bug, or want to improve it—open an issue or submit a pull request. Contributions welcome!

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📄 License

Licensed under the MIT License. See LICENSE for details.