Research on vehicle routing planning based on ant colony algorithm

Abstract

An enhanced ant colony method for omnidirectional mobile vehicle path planning is presented in this paper. The enhanced ant colony algorithm seeks a suitable path that connects the starting and ending sites of the environment while avoiding hazards. The path planning issue, which has been improved to take into consideration the properties of the omnidirectional mobile vehicle, is solved using the ant colony algorithm. Additionally, in the updated approach, the path search is greatly aided by the non-uniform distribution of the initial pheromone and the selection technique with the direction. In order to avoid repetitive searches and reduce the effect of the ant population on the algorithm's performance, the coverage and updating strategy of pheromone is introduced. Furthermore, segmentation and pheromone evaporation coefficient adjustments may be beneficial in achieving a compromise between convergence speed and search capability. This paper's strong mathematical derivation theoretically supports the improved ant colony algorithm, and some numerical simulations are also given to show the effectiveness of the theoretical findings.