Solving path planning problem based on ant colony algorithm

Ant colony algorithm as a new heuristic optimization algorithm, with distributed computing, information positive feedback, and heuristic search features, in solving a variety of combinatorial optimization problems has been widely used. In this paper, with restrictions, to any matter required multi-objective path planning problem using ant colony algorithm for path optimization, the ant colony system is relatively ant system improvements, based on ant colony algorithm path planning problem and pheromone updating the model were established. Simulation results show that ant colony algorithm has strong global search capability, search speed, and better use of the optimal path and a priori knowledge that can effectively overcome the basic ant colony algorithm to learn early stagnation phenomenon, easily with other methods combined beneficial practical application.