Ant Colony Algorithm Based on Local Pheromone Update

The ant colony algorithm is a heuristic bionic algorithm, which can provide better solutions for solving non-convex, non-linear and non-continuous optimum problems. But the ant colony algorithm is easy to fall into local optimum, appear stagnation and other issues. To solve the above problems, this paper presents the ant colony algorithm based on local pheromone update, which adopts the hybrid strategy of city selection strategy, local pheromone update strategy, optimal solution forecast strategy and local optimization strategy to improve the algorithm's performance. Numeric experiment results show that the improved ant colony algorithm can achieve better solutions than the existing solutions on solving some TSP problems.