用自适应的遗传算法求解大学课表安排问题

Adaptive Genetic Algorithms for Solving University Timetable Problem

课程表问题又称时间表问题 (timetable problem) ,是一个多因素的优化决策问题 ,也是组合规划中的典型问题 .本文研究的是大学课表安排问题 ,根据大学课表安排的特点并以优化时间和空间两种资源为目标 ,将课程分为 P、Q两类 .采用鲁棒性比较好的遗传算法 ,并对两类课分别给出其染色体编码和适应度函数 ,并采用了自适应的杂交和变异概率 。

Timetable problem is a multi factor optimized decision problem and is a typical problem in constitution and planning,and so it occupies a central position in school teaching. This thesis employs genetic algorithms which has rather good robust, and takes the arrangement of courses in college as a concrete example.Aiming at optimizing the two resources of time and space, the courses are divided into category P and category Q, and chromosome codes and fitness evaluation are given to each category respectively. With adaptive crossover and mutation probability employed, the experiments verify that this method can produce timetable conforming to requirements.