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| 基于改进遗传算法的智能组卷研究 | |
| 引用本文： | 陈晓敏,梁静,葛宇.基于改进遗传算法的智能组卷研究[J].西南师范大学学报(自然科学版),2012,37(5):98-101. |
| 作者姓名： | 陈晓敏 梁静 葛宇 |
| 作者单位： | 1. 成都电子机械高等专科学校信息与计算科学系,成都,610031 2. 成都电子机械高等专科学校网络中心,成都,610031 3. 四川师范大学基础教学学院,成都,610068 |
| 摘 要： | 通过在遗传算法中引入个体浓度的选择机制和记忆机制,确保了进化过程中种群内个体的多样性,避免局部收敛,保证了算法朝优化方向进化.实验结果表明改进算法能跳出局部收敛,有效避免了早熟产生和遗传退化现象出现. |
| 关 键 词： | 组合优化 智能组卷 遗传算法 局部收敛 |
On Intelligent Test Paper Auto-Generation Based on Improved Genetic Algorithm |
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| CHEN Xiao-min , LIANG Jing , GE Yu.On Intelligent Test Paper Auto-Generation Based on Improved Genetic Algorithm[J].Journal of Southwest China Normal University(Natural Science),2012,37(5):98-101. | |
| Authors: | CHEN Xiao-min LIANG Jing GE Yu |
| Institution: | 1.Information and Computing Science Department,Chengdu Electromechanical College,Chengdu 610031,China;2.Network Center,Chengdu Electromechanical College,Chengdu 610031,China;3.Fundamental College,Sichuan Normal University,Chengdu 610068,China |
| Abstract: | Intelligent test paper auto-generation deals with a multi-objective combinatorial optimization.As a common tool to generate test paper automatically,Genetic algorithm could not achieve the best solution frequently due to the local convergence.In this paper the concentration mechanism and memory mechanism are combined into the genetic algorithm to ensure the population diversity and avoid local convergence.Experiment results show the proposed algorithm can be applied to generate test paper automatically and effectively. |
| Keywords: | combinatorial optimization test paper auto-generation genetic algorithm local converging |
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