Finite element analysis for aviation planning is an important issue in air transportation, and improved route planning optimization can reduce fuel consumption and improve efficiency for aircraft. Nevertheless, the ant colony algorithm displays limitations related to fuel consumption and complexity of computations. This paper aims to enhance the performance of the ant colony algorithm, for simulation of route planning in aviation finite element analysis. For example, the search includes the introduction of multiple optimal pheromone rules, and improving the algorithm parameters. The traditional ACO algorithm was conducted with the improved ACO optimization algorithm in the case of fuel consumption and finite element analysis time, in order to evaluate the performance of the traditional ACO algorithm. The results of this study suggest that the improved ACO algorithm can simultaneously reduce fuel consumption and finite element analysis time, but also the improved ACO algorithm is better than the traditional ACO algorithm.