基于多目标遗传算法的智能组卷系统研究与设计  

Design and Research of Intelligent Test Paper Generation System Based on Multi-objective Genetic Algorithms

作　　者：王孟玉 WANG Meng-yu(Suzhou University,Suzhou 234000,Anhui,China)

机构地区：[1]宿州学院,安徽宿州234000

出　　处：《南宁师范大学学报（自然科学版）》2023年第3期57-62,共6页Journal of Nanning Normal University：Natural Science Edition

基　　金：宿州学院2022年度第二批院级科研平台开放课题项目(编号:2022ykf08)。

摘　　要：为了让考试变得更加科学和公平,在组织考试的各个两节中,有一个重要的举措是整合所有的试题,建立试题库。通过计算机软件进行智能组卷,这个措施在很大程度上提高了工作的效率,保证了试题的准确与客观,从而大大促进了教学质量的持续提升。遗传算法(GA)是一种通过借鉴自然生物进化过程的启发式搜索最优解的算法,组卷问题是多目标优化问题,一般带有多个约束条件。普通的组卷算法运行缓慢、效率低下,试题的质量也参差不齐,要解决这个难题必须改变系统抽取试题的算法,运用遗传算法中关于多目标问题的解决方法,进而可以大大提高智能自动组卷的质量与效率。In order to make the examination more scientific and fair,an important measure is to integrate all the test questions,establish the test database,and organize the test papers intelligently through computer software.This measure greatly improves the efficiency of the work,ensures the accuracy and objectivity of the test questions,and thus greatly promotes the quality of teaching.Genetic algorithm(GA)is a heuristic algorithm for searching the optimal solution by referring to the evolution process of natural organisms.The paper generation problem is a multi-objective optimization problem,which generally has multiple constraints.In order to solve this problem,we must change the algorithm of extracting test questions systematically,and use the method of solving multi-objective problems in genetic algorithm,which can greatly improve the quality and efficiency of intelligent automatic test paper generation.

关 键 词：人工智能 遗传算法 智能组卷系统 多目标优化 

分 类 号：G642[文化科学—高等教育学] TP18[文化科学—教育学]