摘要
针对遗传算法容易陷入早熟收敛,无法自适应具有NP难度的多种约束条件下的排课问题,提出了一种基于量子进化算法的智能化排课算法。对排课的冲突要素和约束条件进行定义,构建了排课模型。引入量子进化算法,基于班级、时间元集合的向量矩阵构造了量子染色体,基于软约束条件的最优解设计了适应度函数,基于量子进化算法的计算框架设计了排课算法。实验表明文中算法具有智能性,能够根据开课任务自动生成排课方案,而且排课的质量和效率都优于文中的对比算法。
Aiming at the flaws that genetic algorithm is prone to fall into the premature convergence and cannot adapt to the NP-hard timetabling problem under multiple constraints,an intelligent timetabling algorithm based on Quantum Evolutionary Algorithm(QEA) is proposed. After defining the conflicts and constraints of curriculum arrangement,the timetabling model is constructed. QEA is introduced,the quantum chromosomes are constructed based on the vector matrix of the classes and time units set,the fitness function is designed based on the optimal solution of the soft constraints,and the timetabling algorithm is designed based on the computational framework of QEA. Experiment results show that the proposed algorithm has intelligence,and can automatically generate the timetable according to curriculum plan,and the quality and efficiency of course arrangement are better than the comparised algorithm in this paper.
作者
张宗飞
ZHANG Zongfei(School of Information Technology and Engineering,Taizhou Vocational&Technical College,Taizhou 318000,China;Collaborative Innovation Center of Applied Information Technology of Taizhou Small and Medium-sized Enterprises,Taizhou 318000,China)
出处
《电子设计工程》
2022年第9期134-138,共5页
Electronic Design Engineering
基金
台州职业技术学院重点资助项目(2022ZD04)。
关键词
量子进化算法
遗传算法
排课模型
排课算法
Quantum Evolutionary Algorithm
genetic algorithm
timetabling model
timetabling algorithm