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基于改进遗传算法的智能组卷方法
引用本文:马德良,陆昌辉,王小乐. 基于改进遗传算法的智能组卷方法[J]. 计算机应用, 2009, 29(7): 1884-1886
作者姓名:马德良  陆昌辉  王小乐
作者单位:国防科学技术大学信息系统与管理学院,长沙,410073
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。

关 键 词:遗传算法  智能组卷  数学模型
收稿时间:2009-01-13
修稿时间:2009-02-11

Intelligent test paper generation based on improved genetic algorithm
MA De-liang,LU Chang-hui,WANG Xiao-le. Intelligent test paper generation based on improved genetic algorithm[J]. Journal of Computer Applications, 2009, 29(7): 1884-1886
Authors:MA De-liang  LU Chang-hui  WANG Xiao-le
Affiliation:College of Information Systems and Management;National University of Defense Technology;Changsha Hunan 410073;China
Abstract: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.
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