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A benchmarking Solution for experimenting with ANT COLONY OPTIMIZATION

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Experimenter—TSPlib: Ant Colony Optimization Benchmarking Suite

Welcome to the Experimenter—TSPlib repository, a comprehensive solution for experimenting with various parameters, settings, configs, and problem instances pertaining to the Ant Colony Optimization (ACO). This repository is a benchmarking suite designed to facilitate experimentation with ACO to solve Traveling Salesman Problems (TSP) using different problem instances and configurations.

Table of Contents

Overview

This solution is built based on a robust ACO implementation inspired by the renowned MSDN Magazine article, designed to parse TSPlib problems and manage an extensive array of experiments efficiently. It serves as an essential tool for researchers and practitioners aiming to analyze the performance of ACO on TSP instances with different configurations and parameters.

Features

  • Powerful ACO Implementation: Based on the well-known MSDN Magazine article, offering robust performance and reliability.
  • TSPlib Parser: Enables problem instantiation from standard TSPlib format.
  • Excel Automation: Incorporates an Excel file for testing automation and the coherent display of results.
  • Extensive Experimentation: Capable of managing an unlimited number of experiments and ants (agents), allowing in-depth analysis and comparisons.
  • Customizable: Users can readily modify parameters, number of ants, and problems for each experiment, ensuring flexibility and adaptability.

Installation

To get started with Experimenter—TSPlib, please clone this repository and ensure that you have the necessary environment to run C# projects.

git clone https://github.com/LeHaroun/Experimenter---TSPlib.git

Usage

  1. Initialize the Solution: Open the solution in a suitable C# IDE, such as Visual Studio, and build the project.
  2. Load TSPlib Instance: Use the TSPlib parser to load the desired TSP instance.
  3. Configure Experiments: Set up experiments with desired parameters, number of ants, and configurations using the provided interface.
  4. Run & Analyze: Execute the experiments and use the Excel file for automated testing and results visualization.

Benchmarking & Experimentation

This solution is tailored for those who are looking to conduct extensive benchmarking and experimentation with ACO on various TSP instances. Users can efficiently manage and compare different settings to analyze the impact of various factors on the solution quality and performance of ACO.

Contributing

  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

License

This project is distributed under the MIT License. See LICENSE for more information.

Contact

Haroun - harounsabry@gmail.com

Project Link: https://github.com/LeHaroun/Experimenter---TSPlib

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