自动组卷的建模和仿真研究

Modeling and Research on Computer Composing Test Paper Intelligently System

研究优化自动组卷问题,自动组卷要求快速获得满足用户的组卷,是一个NP难题,传统组卷组算法存在耗时长、效率低等缺陷,组卷成功率低。为了提高组卷成功率,提出一种遗传算法的智能组卷模型。首先按照试卷难度、区分度、考试总分、考试时间和题型要求建立多目标、多约束数学模型,然后采用遗传算法对数学模型进行求解,得到最优组卷方案。仿真结果表明,相对于其它自动组卷算法,改进遗传算法提高了组卷速度和效率,组卷成功率也相应有所提高,获得组卷质量更优,有效地解决优化自动组卷方法问题。

Research on Optimization of automatic test paper composing,automatic composing test paper need to meet the requirements of users.it is a NP problem,the traditional algorithm are time-consuming,low efficiency,the success rate is very low.In order to improve the success rate of test,this paper put forward a intelligent test paper model based on genetic algorithm.Firtly,the mathematical model is built according to difficulty,discrimination,examination scores,examination time and the topic request,and then the model is solved by genetic algorithm to get the optimal test plan.The simulation results show that,compared with the traditional algorithm,genetic algorithm has improved the speed,success rate and the quality of test paper,it effectively solve the optimization problem of automatic test paper method.