https://github.com/ultimatedoge5/aco-ts

Ant colony optimization algorithm simulation with visualization.
https://github.com/ultimatedoge5/aco-ts

aco algorithm ant ant-colony-optimization ants edge typescript weighted-graphs

Last synced: 16 days ago
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Ant colony optimization algorithm simulation with visualization.

• Host: GitHub
• URL: https://github.com/ultimatedoge5/aco-ts
• Owner: UltimateDoge5
• Created: 2021-04-20T15:17:30.000Z (almost 4 years ago)
• Default Branch: master
• Last Pushed: 2022-11-25T23:14:04.000Z (about 2 years ago)
• Last Synced: 2024-11-10T19:52:29.855Z (2 months ago)
• Topics: aco, algorithm, ant, ant-colony-optimization, ants, edge, typescript, weighted-graphs
• Language: TypeScript
• Homepage: https://ultimatedoge5.github.io/ACO-TS/
• Size: 16.6 KB
• Stars: 3
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# 🐜 ACO-TS

Ant colony optimization algorithm wrote in typescript. You can see the demo in action [here](https://ultimatedoge5.github.io/ACO-TS/).

## About

ACO (Ant colony optimization) algorithm was invented to search for the (probabilistic) optimal path on a weighted graph and to solve the [travelling salesman problem](https://en.wikipedia.org/wiki/Travelling_salesman_problem).

## Algorithm

There are multiple [extensions](https://en.wikipedia.org/wiki/Ant_colony_optimization_algorithms#Common_extensions) of the ant system, but I decided to implement the first and original one. This algorithm is heuristic which means that it will most likely give a better solution with more iterations.

### Control variables

In the ACO  algorithm, we need five variables to control the behaviour of our ants:

* Alpha - states how much impact the pheromones have on the final score of an edge

* Beta - determines how much influence the distance has on the final score of an edge

* Pher - initial value of pheromones

* Pho - defines the rate at which pheromones will evaporate

* Q - indicates the number of pheromones

Using other values than the default will change the behaviour of ants and their ability to determine paths.

## Sources

[Ant colony optimization](https://en.wikipedia.org/wiki/Ant_colony_optimization_algorithms)