Bio-Inspired Computing Project

Overview

This repository contains implementations of bio-inspired algorithms for solving combinatorial optimization problems, specifically focusing on the Knapsack Problem and the Cutting Stock Problem. The algorithms are based on Genetic Algorithms, a nature-inspired optimization technique.

Team Members

• Caio Henrique Araujo Braga

  • Email: chab@cin.ufpe.br

• Iara Yasmim Batista Pereira

  • Email: iybp@cin.ufpe.br

Project Structure

The repository is organized as follows:

• knapsack_problem/: Implementation of Genetic Algorithm for solving the Knapsack Problem.

  • implementacaoKnapsack.py: Python script containing the genetic algorithm for the Knapsack Problem.

  • utils.py: Utility functions used by both problem implementations.

  • analiseKnapsack.ipynb: Python script containing the genetic algorithm for the Knapsack Problem.

Dependencies

The implementations use Python and require the following libraries:

• random: Python built-in library for generating random numbers.
• os: Python built-in library for interacting with the operating system.
• pandas: A library providing high-performance, easy-to-use data structures and data analysis tools for Python.
• matplotlib.pyplot: A plotting module in Python's matplotlib library for creating static, interactive, and animated visualizations.

Contributions

We welcome contributions and feedback. If you have any suggestions or find issues, please feel free to open an issue or submit a pull request.

License

This project is licensed under the MIT License.

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Centro de Informática (CIn), UFPE