智能排课优化算法研究

为解决高校排课优化问题,建立了以教学效果好评度最大化为优化目标的排课数学模型.针对传统遗传算法的不足,给出了一种混合遗传算法,该算法不仅能够对传统遗传算法的交叉率、变异率进行自适应改进,还能够实现冲突检测与消除功能.测试结果表明,该算法比传统的遗传算法、贪婪算法和蚁群算法耗时短,而且教学效果好评度最高,这说明该算法能有效缩短排课时间,提高排课质量和效率,实现高校排课智能化.

Research of optimization algorithm for course timetabling problem

In order to solve the problem of university course timetabling, a mathematic model was established based on the objective function of maximum teaching effect praise degree. Aiming at the shortcoming of traditional genetic algorithm, a hybrid genetic algorithm which combined with self-adaptive crossover and mutation were put forward. The conflict detection and elimination function were realized. The test result show that hybrid algorithm was faster than traditional genetic algorithm, greedy algorithm and ant colony algorithm but the highest teaching effect praise degree. It proved that the algorithm shorten the time consuming, improve the quality and implementation the intelligence of course timetabling effectively.