Genetic Algorithm for Cutting and Packing Optimization

🔍 Overview

This repository presents an implementation of a Genetic Algorithm (GA)-based approach for solving the Cutting and Packing Problem. The goal is to optimize object placement within a constrained space, reducing material waste while maximizing efficiency. This algorithm is particularly useful in manufacturing, logistics, and material utilization applications where efficient space management is crucial.

⚙️ Features

✅ Implements Genetic Algorithm (GA) for solving the cutting and packing problem
✅ Supports object rotation (90-degree adjustments) to improve placement efficiency
✅ Utilizes roulette wheel selection, single-point crossover, and mutation for solution refinement
✅ Provides visualization tools for analyzing placements and results
✅ Achieves 30-50% waste reduction compared to random placement methods
✅ Includes a configurable structure to test various object arrangements

📂 Repository Contents
• cizim.py / cizim2.py → Visualization tools for placement analysis
• prg1.py - prg5.py → Core GA implementation and optimization functions
• rulet.py → Roulette selection mechanism for GA
• bilgi.txt → Input data and configuration parameters
• README.md → Documentation and usage instructions

📥 Installation & Usage

To use this project, clone the repository and run the main script:

git clone https://github.com/bturkoglu/placement-problem-with-genetic-algorithm.git
cd placement-problem-with-genetic-algorithm
python cizim2.py

Modify the configuration parameters in bilgi.txt to test different object arrangements.

📊 Experimental Results

The algorithm was tested on multiple object configurations, demonstrating:
✔ 30-50% reduction in material waste compared to random placement
✔ Improved adaptability over traditional greedy heuristic methods
✔ Optimized space utilization with evolutionary computation techniques

📝 Citation & Reference

This research has been submitted to ICATCES 2025 Conference. The abstract can be accessed here:
📄 [ICATCES 2025 Abstract](Abstract Link - After Acceptance)

For academic citation, please use the following format:
B. Türkoğlu, “A Genetic Algorithm-Based Approach to the Cutting and Packing Problem,” ICATCES 2025, Karabuk, Turkey.

📎 License

This project is released under the MIT License. You are free to use, modify, and distribute the code with proper attribution.

🔗 Full Implementation & Documentation

🔗 GitHub Repository