Intelligent Decision Support System for Electric Power Material Transportation Based on GA Algorithm

With the rapid development of the economy, the logistics and transportation network of large goods has some problems, such as low level of informatization and chaotic transportation scheme. The research focuses on power logistics transportation, proposes an intelligent decision support system, and uses genetic algorithm to optimize and solve the path selection module of the system. In the validation of the path selection model and optimization solution, the results showed that the average absolute percentage error value based on the probability matrix factorization algorithm was the lowest at 12.15%, while the highest value of the genetic algorithm was 8.32%, far lower than the former's 3.83%. The path selection algorithm is applied to intelligent decision support systems, and the clustering algorithm based on classification attributes has the highest average recommendation accuracy of 72.56%, while the genetic algorithm has the highest accuracy of 95.67%. Therefore, it has been proven that the intelligent decision support system for power material transportation based on genetic algorithm has superiority and feasibility.