一种改进遗传算法的自动组卷系统优化研究  

Research on Optimization of Automatic Test Paper Generation System Based on Improved Genetic Algorithm

作　　者：刘雅莉 LIU Yali(Faculty of Economics and Management,Shangluo University,Shangluo,Shanxi 726000,China)

机构地区：[1]商洛学院经济管理学院,陕西商洛726000

出　　处：《微型电脑应用》2020年第8期28-30,40,共4页Microcomputer Applications

基　　金：教育部产学研协同育人项目(201702119071)。

摘　　要：基于改进的传统遗传算法完成了一种自动组卷系统的设计,使用改进遗传算法构建了一种包括试题编码方法、选择交叉算子、设置变异等环节在内的智能组卷策略,对组卷过程的适应度函数通过加权目标函数的建立完成优化处理,进而实现良好的适应度的获取,选择操作环节通过结合运用保优策略和轮盘赌方法得到了进一步优化,在实现快速成功组卷的同时提高了组卷质量。根据系统的仿真实验证实了自动组卷系统的可行性。This paper has completed the design of an automatic test paper generation system based on improved traditional genetic algorithm, and used the improved genetic algorithm to construct an intelligent test paper generation strategy that includes test coding methods, selection of crossover operators, and setting of mutations. The fitness function of the test paper composition process is optimized through the establishment of a weighted objective function, thereby achieving a good fitness. The selection operation is further optimized by combining the use of a premium strategy and a roulette method, achieving rapid success. At the same time, the quality of the test paper is improved. And the simulation experiments verify the practicability of the test paper algorithm.

关 键 词：遗传算法 组卷系统 优化分析 

分 类 号：TP291[自动化与计算机技术—检测技术与自动化装置]