基于遗传算法的高考志愿填报排序问题的研究

Application of Genetic Algorithm on Optimal Sequence of College Entrance Examination Voluntary Report

针对高考志愿填报录取最优化、最佳匹配问题,提出了基于遗传算法搜索最优解的解决方案。该方案模拟物种自然选择和遗传进化过程,将不同考生的高考志愿按录取结果利益最大化进行排序。在可选择院校数量相同的情况下,对不同考生考试成绩的数据通过程序不断进行智能优化和迭代,志愿排序结果趋于稳定,且达到最佳匹配。其不但满足考生的实际需求,而且达到志愿填报利益最大化的目的。该方法采用涵盖985、211、普通院校的10所高校的实际数据进行测试,结果表明,遗传算法可以用来求解最优高考志愿填报排序问题,且具有很高的准确率和适应度。

We proposed a method according to genetic algorithm(GA),which aims at finding the best and optimal plan for the college entrance examination voluntary report.The project simulates the process of natural selection and genetic evolution,ranking college aspirations of different examinees,so that they will have maximum benefits.Under the condition that the amount of selectable universities is the same,the sequences of different examinees' data tend to be stable by using the procedure to iterate and optimize intelligently.These sequences are stable and optimal,which can meet the practical needs of the examinees and achieve the goal of maximizing the benefits.The method adoptes the data from ten universities including 985,211,and common colleges to test and record.The results indicate that GA can be used to decide the best and optimal sequence for the college entrance examination voluntary report and it has high accuracy and fitness indeed.