基于改进遗传算法的排课问题研究

针对遗传算法在解决排课问题中易陷入局部最优解的缺陷，提出一种改进的遗传算法。在传统遗传算法基础之上，融合模拟退火思想，使交叉得到的子代以一定概率进入下一代，并对传统的基于概率的计算方法进行改进, 编排出优质的课表。实验结果表明改进算法不仅加快了前期进化速度，而且解决了遗传算法后期易陷入局部最优解的缺陷。

Research on Curriculum Schedule Arrangement Based on Improved Genetic Algorithm

The conventional genetic algorithm is easy to fall into the local optimal solution during the curriculum schedule arrangement. This paper introduces an improved genetic algorithm that can solve this problem. Based on conventional genetic algorithms, the improved genetic algorithm fuses the simulated annealing. It makes the progeny, obtained by crossing,enter the next generation with a certain probability. The improved genetic algorithm can also improve the conventional methods of this probability calculation, which can make the course schedule have high quality. The experimental results show that the improved algorithm has not only accelerated the evolutionary rate of the early stage, but also solved the shortcomings of the genetic algorithm in the local optimal solution.