Abstract: The university timetabling arrangement problem is converted into a multi-object constrained optimization problem. Immune clonal algorithm with hybrid code is used to optimize it. Similar vector-based selection method is used to suppress concentration of antibodies for avoiding premature convergence. Simulation result shows that the algorithm can provide better results in timetabling arrangements, users satisfaction and run time.

Key words: timetable arrangement problem, immune clone algorithm, hybrid coding, adaptive mutation, constrained optimization

摘要： 将高校课表编排问题转化为带约束的多目标优化问题，基于混合编码，应用免疫克隆算法对随机课表编排方案进行优化。通过基于相似性矢量矩的选择方法抑制抗体浓度，保证种群多样性，避免免疫克隆算法陷入早熟收敛。仿真结果表明，该方案在课程合理性、总体满意度和运行时间方面均能取得较好的效果。

关键词: 课表编排问题, 免疫克隆算法, 混合编码, 自适应变异, 约束优化

CLC Number: 

• TP18