Path planning of intelligent factory based on improved ant colony algorithm

In order to solve the problem that the collection of data is not fast due to the route selection in the important links of intelligent factory, such as collecting dynamic data by using AGV, production scheduling, logistics transportation, etc., an improved ant colony algorithm is used to improve the question. The improved ant colony algorithm is a combination of ant colony algorithm and particle swarm optimization algorithm, so that ants no longer only rely on pheromone communication, and use the particle swarm algorithm to generate the initial distribution of pheromone of the path to solve the blindness of the early ant colony algorithm. Through the simulation in the map and compared with the test results of the fundamental ant colony algorithm, the experimental data illustrate that the improved ant colony algorithm can find a shorter path and reduce the path length.