摘要
论文深入分析了年度排课问题的特点,提出了一种基于改进遗传算法的求解方法。该方法通过分析适应度与编码之间的内在关系,对常规遗传算法的杂交和变异操作进行了改进,提出了基于子适应度的纵向基因杂交法和自适应变异策略等方法。仿真结果表明该改进的遗传算法相比于常规遗传算法在求解年度排课问题时性能有了较大的提升。
Annual timetabling problem was analyzed detailedly, and an improved genetic algorithm was proposed to solve this problem. Longitudinal gene crossover method based on sub-fitness and adaptive aberrance strategy was proposed by analyzing the intrinsic relation between fitness and code. Simulation results indicated that this improved genetic algorithm can solve annual timetable problem more effective than common genetic algorithm.
出处
《计算机与数字工程》
2016年第8期1619-1624,共6页
Computer & Digital Engineering
关键词
遗传算法
年度计划
排课问题
自适应变异策略
genetic algorithm, annual plan, timetable problem, adaptive aberrance strategy
