基于粒子群算法的机房排课问题研究  

The Research on Computer Room Scheduling Based on Particle Swarm Optimization

作　　者：王文君[1] WANG Wen-jun(Minjiang University,Fuzhou 350108,China)

机构地区：[1]闽江学院,福州350108

出　　处：《长春工程学院学报（自然科学版）》2019年第4期99-102,共4页Journal of Changchun Institute of Technology：Natural Sciences Edition

基　　金：福建省本科教学工程项目(闽教高[2012]160号)。

摘　　要：排课问题一直以来都是一个NP难题。针对该NP难题,如何解决当前高校日益紧张的教学资源,实现机房的合理、高效安排,是一项烦琐的工作。对此,结合排课问题的影响因素,构建机房排课数学模型,改进现有的PSO粒子群算法,将种群平均划分,然后再用标准PSO算法对机房排课模型进行求解,从而得到在硬约束和软约束下的机房排课最优解。结果表明,改进的PSO算法与传统的MMAGA算法相比,其适应度函数值较高,具有良好的编排质量。Course scheduling has always been an NP problem.In view of this NP problem,how to solve the increasingly tense teaching resources in colleges and universities and realize the rational and effective arrangement of computer rooms is a tedious task.Thereafter,this paper combines the influencing factors of the course scheduling problem,constructs a computer room scheduling mathematical model,and then optimizes the particle swarm algorithm.It divides the population evenly,and solves the computer room scheduling mathematical model by using standard PSO algorithm,so as to obtain the optimal solution under hard and soft constraints.The results show that the PSO algorithm has higher fitness function value and better arrangement quality than the traditional MAGA algorithm.

关 键 词：粒子群算法 NP问题 数学描述 机房排课 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]