Research on Hybrid Intelligent Algorithm for Comprehensive Evaluation of Aviation Logistics Performance

To evaluate the performance of air logistics service providers and manage them comprehensively, and realize the purpose of high efficiency of the whole logistics activities, this paper proposes a hybrid intelligent algorithm for the evaluation of air logistics service providers for aviation enterprises by discussing the current situation and existing problems of the evaluation of air logistics service providers of a freight company. Based on determining the weights of several key factors evaluation indexes of aviation logistics enterprises, and aiming at the shortcomings of BP neural network in randomly initial weights and thresholds, the global search function of genetic algorithm is used to assign the optimal weights and thresholds of BP neural network. The calculated performance score is taken into BP neural network as a sample for correction to eliminate subjective factors. In the experimental part, the trained neural network model is used for formal performance evaluation. The results show that the performance evaluation method based on improved genetic algorithm has the characteristics of high speed and high accuracy, which is of great significance for the establishment of a scientific and effective aviation performance evaluation system.