Ant Colony Optimization (ACO) algorithm for Traveling Salesman Problem (TSP) implemented in Julia.
Input data for TSP can be defined in a form of a distance matrix. The matrix can be defined as a Julia array or loaded from a file.
Matrix must have Inf as a value for non-existing edges.
Results for D1 matrix from data/dists.jl.
Datasets from TSPLIB database are also supported.
Optimization was performed on Wi29 dataset.
During the experiments the suboptimal tour of length 27760.0 was found in just 100 iterations with 50 ants.
The optimal tour of length 27603.0 is illustrated below.
