An effective initialization strategy of pheromone for ant colony optimization

Aiming at the poor performance of convergence of ant colony optimization (ACO), in this paper, a novel pheromone initialization strategy of ACO for the traveling salesman problem (TSP) is put forward. More precisely, the pheromone matrix of a specific ACO algorithm is initialized by the minimal spanning tree (MST) information. Simulation results demonstrate that the proposed strategy could improve the convergence performance of ACO both in term of quality of solution and speed of convergence.