摘要
组卷问题是一个多约束多目标优化问题。建立了一种新的试卷矩阵数学模型,提出了改进的遗传算法编码方式,并通过改进初始群体的产生方法和遗传算子,有效提高了遗传算法的收敛速度,并较好地避免了局部收敛现象。实验结果表明,在试题库试题数量适中、分布合理的情况下,本算法产生的试卷能够很好满足各项组卷指标。
The test paper generation is a multi-constraint and multi-objective optimization issue. A new mathematical model of intelligence test paper generation system was set up. To avoid slow-convergence and local convergence of simple genetic algorithm （SGA）, a kind of improved genetic algorithm was proposed in this paper. The experimental results show that the new method is more efficient and effective to deal with the problem of intelligent test paper generation.
出处
《计算机应用》
CSCD
北大核心
2009年第7期1884-1886,共3页
journal of Computer Applications
关键词
遗传算法
智能组卷
数学模型
Genetic Algorithm （GA）
intelligent test paper generation
mathematical model
