antprobe.js

Ant Colony Optimization(ACO) by Javascript.

蟻コロニー最適化法による巡回サラリーマン問題解法のJavaScript実装。

What is ACO?

ACO is algorithm to solve optimization problem as metaheuristics.

• ant colony optimization algorithms - wikipedia(en)
• 蟻コロニー最適化 - wikipedia(ja)

this library find shortest path by ACO.

Demo

This demo need WebWorker supported.

Demo site

Validation

• google Chrome 29 later.

How to use Demo

push start

console

• start/stop
  • start or stop calculation.
• reset
  • reset status to initinal state.
• City configuration
  • adittion
    • apply custom city number.
  • Number of cities
    • set number of cities.(optimize your processivity.)
• Ant configuration
  • apply
    • apply custom configuration.
  • Ant priority heuristic
    • set ant's criterion of heuristic. This is susceptible to distance.
  • Ant priority pheromone
    • set ant's criterion of heuristic. This is susceptible to pheromone mapping.
  • Ant colony scale
    • set number of ants.(optimize your processivity.)
  • Ant pheromone density
    • set influence of one ant.
  • Pheromone evaporation speed
    • set disappearance speed of weited routes.

view

• Touch cities and moving, fix city position. After it, push "apply".

License

MIT License