No ant sees the whole map, yet the colony finds a near-optimal route. Pheromone trails reinforce short paths and evaporate off long ones — swarm intelligence solving the Traveling Salesman Problem.
Ant Colony OptimizationLive
swarm intelligence · TSP
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Simulated ants lay pheromone (cyan) on short routes; trails evaporate over time so good paths reinforce and bad ones fade. The colony collectively finds near-optimal tours of the Traveling Salesman Problem — the green loop is the best so far.
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How it works
Ant Colony Optimization sends many simple agents to build tours, biased toward strong pheromone and short edges. Each ant deposits pheromone inversely proportional to its tour length, and evaporation prevents premature convergence. Over many iterations the collective trail converges on an excellent solution to this classic NP-hard problem.
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The math, the assumptions, real-world uses, or a code translation — explained for this exact simulation.
Is this ant colony optimization TSP tool really free?▾
Yes. Ant Colony Optimization runs entirely in your browser using your device's own compute, so local use is free forever. You only pay Compute Tokens if you scale a job to the cloud.
Do I need to install anything?▾
No. Everything runs client-side in a modern browser — no downloads, no license, no account required to start.
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How accurate are the results?▾
The solver uses established numerical methods, but results are for research and educational purposes and should be validated against experiment or professional review before you rely on them.