基于遗传算法的大学计算机基础自动组卷方法

摘要

Since the traditional test paper generation method has the problems of low efficiency and low success rate,an genetic algorithm based automatic test paper generation method of university computer foundation is designed. The fitness function of automatic test paper generation of university computer foundation is designed. The coding is used to handle the related constraint conditions of question types and quantity distribution in the process of test paper generation. The selection operator,crossover operator and mutation operator are designed. The fitness is taken as the indicator to evaluate the population diversity. The crossover probability and mutation probability are solved,and the terminal condition of genetic algorithm is given. The experimental results show that the proposed method can improve the efficiency and success rate of automatic test paper generation method of university computer foundation.%针对传统组卷方法效率、成功率低等难题,设计基于遗传算法的大学计算机基础自动组卷方法.首先设计大学计算机基础自动成卷适应度函数,采用编码对组卷过程中题型及与其数量分布相关的约束条件进行处理,然后设计选择算子、交叉算子以及变异算子,将适应度作为评价群体多样性的指标,求出交叉概率与变异概率,给出遗传算法终止条件.实验结果表明,该方法提高了大学计算机基础自动组卷方法的效率和成功率.