Overview of Pheromone Control Method based on Ant Colony Algorithm in Wireless Communication

Ant colony optimization has become an important tool for solving complex optimization problem, and has been widely applied in many areas. In ant colony algorithm, pheromone is the key to realize swarm intelligence, and it is an important medium for artificial ants to realize indirect communication and cooperation between themselves. In order to improve the overall performance of ant colony algorithm and improve the pheromone control method, this paper studies the pheromone control method and its diffusion model. First, this paper introduces the research significance and research status of pheromone control method. Then, the new methods of pheromone control are reviewed, such as Max-min Ant System (MMAS), Ant Colony System (ACS) and Nearest Neighbor Ants (NN-Ants), and their advantages and disadvantages are analyzed and compared. Finally, combining with some related work has been carried out in the research group, the research progress of pheromone diffusion model is given based on path and correlation distance of multidimensional knapsack problem application. The existing research shows that the control strategies on pheromone, which includes its retaining, initialization, updating and evaporation, influence the performance of ant colony algorithm significantly.