基于遗传算法的在线考试系统自动组卷策略优化

Strategic Optimization of Auto-generating Test Paper for Online Test System Based on Genetic Algorithm

该文在对试卷结构进行分析的基础上,利用遗传算法的全局寻优和收敛速度快的特点,设计一种用于自动组卷的自适应遗传算法,建立和描述了组卷问题的染色体数目和适应度函数,实施了问题的遗传操作。采用遗传算法从题库中抽出一组最佳解或抽出一组非常接近最佳解的实体,并进行了大量组卷实验。实验结果表明,自适应遗传组卷算法可行、高效,具有较好的适用性,提高了在线考试系统自动组卷的效率。同时减轻了教师的负担,满足了教育教学的要求。

This paper,on the basis of analyzing the structure of the test paper,designs an adaptive genetic algorithm for auto-generating test paper,establishes and describes the number of chromosome and fitness function for the test paper problems,implements genetic operations by the use of genetic algorithm global optimization and convergence speed.Using the above-said genetic algorithm from the item bank,a set of optimal solution or approximate one of the entity is selected,and a large number of test experiments are implemented.The results show that the adaptive genetic algorithm is feasible,effective and adaptive,which promote the efficiency of auto-generating test paper for online test system,ease the burden on teachers and satisfy the teaching requirement.