遗传算法在智能组卷系统中的应用研究

为更好地解决遗传算法在智能组卷过程中出现的早收敛问题,以及组卷质量和组卷速度呈负相关的问题,提出一种基于分段整数编码、多点交叉的遗传算法.通过大量实验,有针对性地对该算法中的编码结构、选择算子、交叉算子和变异算子进行优化设计;对相关控制参数进行合理调整,实验结果表明,该算法不仅有效地提高了组卷质量和组卷速度,而且具有很好的收敛性.

Application of the genetic algorithm in the intelligent test paper generation system

In order to resolve the problems in the process of applying the genetic algorithm in the intelligent test paper generation such as the premature convergence and a negative correlation between the quality and the velocity of test paper generation,this paper proposes a genetic algorithm based on sub- sectional integral encoding and multi- point crossover. Targeting these problems,this paper optimizes the design factors of the encoding structure,the selection operator,the crossover operator and the mutation operator in the application of the genetic algorithm in the intelligent test paper generation. By appropriately adjusting the relevant parameters,experiments show that the genetic algorithm not only effectively enhances the quality and the velocity of the test paper generation,but also enjoys a good convergence.