https://github.com/talhaahussain/ant-colony-optimisation
Continuous Assessment for ECM3412 - Nature-Inspired Computation, set by Prof. Ayah Helal (Year 3, Semester 1). Implements the ant colony optimisation algorithm to address the travelling salesperson problem for two given networks.
https://github.com/talhaahussain/ant-colony-optimisation
ant-colony-optimization evolutionary-algorithms
Last synced: 8 months ago
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Continuous Assessment for ECM3412 - Nature-Inspired Computation, set by Prof. Ayah Helal (Year 3, Semester 1). Implements the ant colony optimisation algorithm to address the travelling salesperson problem for two given networks.
- Host: GitHub
- URL: https://github.com/talhaahussain/ant-colony-optimisation
- Owner: talhaahussain
- License: mit
- Created: 2024-04-07T06:40:03.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-07-02T10:13:35.000Z (over 1 year ago)
- Last Synced: 2025-02-21T07:41:32.436Z (8 months ago)
- Topics: ant-colony-optimization, evolutionary-algorithms
- Language: Python
- Homepage:
- Size: 2.07 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# ant-colony-optimisation
Continuous Assessment for ECM3412 - Nature-Inspired Computation, set by Prof. Ayah Helal (Year 3, Semester 1). Implements the ant colony optimisation algorithm to address the travelling salesperson problem for two given networks. Please see `results/results.pdf` for insights on results and written answers to questions.
This work received a final mark of 70/100.
Please see `specification.pdf` for specification.
### Prerequisites
Project was developed in Python 3. Install prerequisites with:
```bash
pip install -r requirements.txt
```
`aco.py` and `elitist-aco.py` require `ant.py` and `load_data.py` to run.
### Usage
The program is executed from `aco.py`. To run the program, please use
```
python aco.py
```
To run `elitist-aco.py`, please use
```
python elitist-aco.py
```
Details on modifying parameters/variables to reflect experiments can be found in the Python source code.
This is done at the call of the main method, right at the bottom of the script.
### Results
Results shown in `results/results.pdf` and the associated text files, which can be found in `results/BurmaResults/` and `results/BrazilResults/`. Execution durations are also stored in the text files, and images are included in the directories.