遗传算法在组卷系统中的应用  

Application of Genetic Algorithm in Test Paper System

作　　者：师小霞[1] 李世豪[1] Shi Xiaoxia;Li Shihao(Pingdingshan Industrial College of Technology,Pingdingshan Henan 467000,China)

机构地区：[1]平顶山工业职业技术学院,河南平顶山467000

出　　处：《信息与电脑》2018年第17期25-26,共2页Information & Computer

摘　　要：网上考试系统中组织试卷的核心工作是抽取题目,当需求以及试题表均单一时,抽题过程采用随机数方法,配合单层循环即可实现。当需求复杂时,试卷的组成是一定数量的题目,题目有类型、所属单元和难度等级等属性,须在遗传算法的框架内使用迭代。染色体的编码采用粗粒度的十进制,目标函数的定义和个体适应度的计算方式是算法应用的核心,需用适应度限定系数矩阵中的值约束个体特征值,实现个体适应度和目标函数同步。The core work of organizing the examination papers in the online examination system is to extract the questions.When the demand and the question sheet are all single,the random number method is used to solve the questions,and the single-layer cycle can be implemented.When the requirements are complex,the composition of the test paper is a certain number of topics.The topics have attributes such as type,unit,degree of difficulty,etc..Iterations must be used within such a framework as genetic algorithms.Chromosome coding adopts coarse-grained decimal.The definition of objective function and the calculation of individual adaptability are the core of the algorithm application.The value in the fitness limit coefficient matrix is used to constrain individual eigenvalues to achieve individual adaptability and objective function synchronization.

关 键 词：自动组卷 多向量 遗传算法 适应度限定系数 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]