基于灰狼算法的高校实验课网络排课问题研究  

Research on Network Course Scheduling of College Experimental Courses Based on Grey Wolf Algorithm

作　　者：阮德致 梁荣[1] 迟军[1] 季英萍[1] RUAN Dezhi;LIANG Rong;CHI Jun;JI Yingping(Hongzhou Bay Automobile Institute,Ningbo Institute of Technology,Nongbo 315000,China)

机构地区：[1]宁波工程学院杭州湾汽车学院,浙江宁波315000

出　　处：《微型电脑应用》2021年第5期76-78,共3页Microcomputer Applications

基　　金：宁波工程学院“十三五”校级教学改革研究项目(201911)。

摘　　要：为提高高校实验课网络排课的排课效率,节约排课时间和减少工作量,提出了一种基于灰狼优化算法的高校实验课网络排课算法。首先,从教师、课程、班级和课堂等方面对网络排课问题进行描述并建立数学模型;其次,运用GWO算法对网络排课数学模型进行优化求解。研究结果表明,与GA和PSO相比,GWO可以有效提高网络排课的效率,节约网络排课时间,从而为网络排课提供了新的方法。In order to improve the efficiency,save the time and reduce the workload of online course scheduling of experimental courses in colleges and universities,a new online course scheduling algorithm based on grey wolf optimization(GWO)algorithm is proposed.Firstly,this paper describes the problem of online class scheduling from the aspects of teachers,courses,classes and classes,and establishes a mathematical model.Secondly,GWO algorithm is used to optimize and solve the network class scheduling mathematical model.The results show that compared with GA and PSO,GWO can effectively improve the efficiency of online class scheduling and save the time of online class scheduling,thus,provides a new method for online class scheduling.

关 键 词：粒子群算法 网络排课 灰狼优化算法 冲突检测 目标函数 

分 类 号：G642.4[文化科学—高等教育学]