Ascent Science ACO plugin

Install version 0.1.1 with python -m pip install ascent-science-aco==0.1.1, then use ascent.combinatorial.ACOOptimizer(...).

The solver implements the Ant System update rule for directed and symmetric travelling-salesperson instances. The result exposes three convergence series:

• history: best-so-far distance (monotonically non-increasing)
• iteration_best_history: best distance found in each iteration
• mean_history: mean distance of all ants in each iteration

0.1.1

• Uses the Ant System transition probability with pheromone and inverse-distance heuristics.
• Applies evaporation and Q / L deposits after every iteration.
• Preserves directed pheromone updates for asymmetric matrices and mirrors deposits for symmetric matrices.
• Returns the best-so-far convergence history used by the experiment chart.