An Intelligent Teaching Test Paper Generation System Based on Ant Colony Hybrid Genetic Algorithms

In this paper, the problem of intelligent test paper generation is discussed, and the advantages and disadvantages of current commonly used intelligent test paper generation algorithms are analyzed. By comparing genetic algorithm with ant colony algorithm, it is found that the two algorithms have complementary advantages and they can be integrated organically. On this basis, an intelligent test paper generating strategy based on hybrid genetic algorithm and ant colony algorithm is proposed. The experiments show that the convergence speed of hybrid test paper generating strategy is faster than that of single genetic algorithm and ant colony algorithm. Compared with single genetic algorithm and ant colony algorithm, the efficiency and success of hybrid test paper generating strategy are greatly improved, which has better practicability.