摘要
针对高校排课问题,本文提出了一种基于历史课表的优化遗传算法。算法采用历史课表信息构造优秀的基因个体,采用新课表与历史课表相似度作为评价种群的适应度函数。实验结果表明,相对传统遗传算法,本文提出的算法收敛速度较快,排课结果较优。
In order to solve the problem of arranging courses in Colleges and universities,this paper proposes an optimized genetic algorithm based on the history timetable.The algorithm uses the history curriculum information to construct excellent gene individuals,and uses the similarity between the new curriculum and the history curriculum as the fitness function of the evaluation population.The experimental results show that the algorithm proposed in this paper has faster convergence speed and better scheduling results than the traditional genetic algorithm.
作者
王天才
杨远贵
徐倩
袁慧宇
WANG Tiancai;YANG Yuangui;XU Qian;YUAN Huiyu(Department of Physics and Electronic Information,Huaibei Normal University,Huaibei,China,235000;Information College,Huaibei Normal University,Huaibei,China,235000)
出处
《福建电脑》
2022年第9期28-32,共5页
Journal of Fujian Computer
基金
2020年安徽省高等学校省级质量工程重点项目基金(No.2020jyxm1699)
2020年安徽省高校省级质量工程项目基金(No.2020kcszyjxm215)资助。
关键词
排课算法
遗传算法
适应度函数
历史课表
教务系统
Automatic Course Scheduling
Genetic Algorithms
Fitness Function
History Class Schedule
Educational Administration System
