基于局部搜索的遗传算法求解自动组卷问题

针对目前大多数组卷系统所考虑的约束条件不完善、 组卷结果不理想问题. 提出一种基于局部搜索的遗传算法（GALS）, 解决了传统组卷约束不完善等缺点, 并得到了较好的组卷结果. 该算法采用基于按题型分段的编码方式, 3个遗传算子分别采用如下策略： 按题型分段交叉策略, 保证全局搜索能力及交叉后各题型被选题数不变； 基于禁忌表局部搜索的变异机制, 对题库进行随机关联搜索, 提高了算法搜索能力； 采用组合优化进化算法的μ+λ选择策略, 有利于算法局部搜索. 实验结果表明, 相同迭代次数下, 新算法找到的最优解明显优于传统的组卷算法.

Genetic Algorithm with Local Search for Automatic Test Paper Generation

In most of the automatic test paper generation system,the constraint conditions are not perfect,and the results are not ideal.In view of this situation,we put up a new method called genetic algorithm with local search;it can solve the problem of constraint conditions which are not perfect, and can achieve the better results,after the teacher's certification,it proves to be applied to the actual teaching.The algorithm uses the subsection encoding based on the type of questions.Three genetic operators adopt t...