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Collective Problem Solving

Ant Colony Optimization for the Traveling Salesman Problem

Cities

Best Path

Pheromone Trails

Number of Cities

Number of Ants

Pheromone Importance (α)

1.0

Distance Importance (β)

3.0

Evaporation Rate (ρ)

0.10

Optimization Progress

Iteration: 0

Current Best: -

Global Best: -

Improvement: -

How ACO Works

Ants explore paths probabilistically, preferring edges with more pheromone (α) and shorter distance (β). After completing tours, ants deposit pheromone inversely proportional to tour length. Pheromone evaporates (ρ) to prevent premature convergence. Over time, the colony converges on near-optimal solutions.