Efficiency Analysis on the Path Optimization of Ant Colony Algorithm Based on Neural Network Optimization

摘要

The issue of path optimization often has multiple objectives and multiple limited conditions, which is to solve integrated issues with a certain complexity. Often a single algorithm cannot perfectly solve the problem of the optimum path selection in the path optimization. Through optimizing the ant colony algorithm, this paper introduces neural network into the complex model, trains the parameters of the ant colony algorithm, and obtains a high-precision model and new solving idea of path optimization. By organically integrating algorithms, the paper conducts innovation and improvement on the existing algorithm, and enhances its application reliability and accuracy. And it also well explains and solves the efficiency problems in three-dimensional path planning.