基于改进遗传算法的组卷算法研究与应用  

Research and Application of Test Paper Generation Based on The Improved Genetic Algorithm

作　　者：嵇春梅[1] 

机构地区：[1]盐城纺织职业技术学院,江苏盐城224005

出　　处：《数字技术与应用》2011年第11期130-131,133,共3页Digital Technology & Application

基　　金：江苏省高等教育教学改革研究课题(2011JSJG429)

摘　　要：在基本遗传算法的基础上,对编码策略、适应度函数、遗传算子进行了改进,增加了优良个体的保留机制,有效地解决了智能组卷中的约束优化问题,提高了组卷效率。实践结果表明,改进的算法具有较好的通用性、自适应性、收敛性和全局优化性,已应用于试题库系统的组卷,并取得了良好的效果。On the basis of genetic algorithm,by improving the coding strategies,the fitness function,the enetic operators,and increasing the retention mechanism of excellent individuals,it could effectively solve the problem of restriction optimizingin the process of intellect test paper combination.,and Improve the efficiency.prove that this kind of genetic algorithm has good generality,adaptivity,convergence,and the characteristics of the global optimization.It Has been applied to the test paper generation of the database system,and has achieved good effects.

关 键 词：遗传算法 约束条件 适应度函数 遗传算子 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]