基于遗传算法的组卷研究

Studies in exam paper generating based on the genetic algorithm

为了克服遗传算法在自动组卷中容易"早熟收敛"的现象,引入局部爬山方法以及动态参数自适应调整方法进行改进,给出了算法流程图.利用改进的算法对淄博职业学院《大学英语》题库进行自动组卷实验,实验证明,改进后的算法较好地解决了原有算法的缺陷.

In order to overcome the problem of premature convergence in genetic algorithms for automatic test generation,a local hill climbing approach is employed to adaptively tune the dynamic parameters in genetic algorithms.We present the algorithmic workflow and apply the new algorithm to automatically generate tests with the question database of the undergraduate English course at Zibo Vocational College.Experimental results show that the new algorithm indeed alleviates the problem of premature convergence significantly.