Path optimization design of teaching resource sharing platform based on ant colony optimization algorithm

Abstract

Aiming at issues such as slow convergence of algorithms and low utilization of overall resources in the current research of path optimization design of teaching resource sharing platform, this article applied the path optimization method of teaching resource sharing platform on the basis of ant colony optimization (ACO) to address the issue. By transforming the path optimization problem of the teaching resource sharing platform into a graph theory problem and adjusting the parameter configuration of ACO, the slow convergence speed of the algorithm in the path optimization of the teaching resource sharing platform was optimized, thereby improving the overall resource utilization rate. The experimental findings showed that after 300 iterations, the transmission delay of the path optimization method for the ACO-based teaching resource sharing platform was within 10 ms; the bandwidth utilization rate was over 90%; the path reliability was over 85%; the computation time was within 0.1 s. Moreover, by comparing with other algorithms, it was found that the ACO algorithm was at its best in all data metrics. The monitoring and survey results of the teaching resource sharing platform show that the distribution of teaching resources on the platform has been effectively optimized after the optimization of ACO, and user satisfaction and ratings have significantly improved.