基于改进人工蜂群算法的高校自动排课问题的研究

Research on Automatic Course Scheduling in Universities Based on Im-proved Artificial Bee Colony Algorithm

为了解决人工蜂群算法在排课问题上无法跳出局部最优的问题,提出一种基于混沌算法的混合人工蜂群算法(HABC算法)。HABC算法在寻优过程中重视食物源对蜂群的影响,增加邻近区域内对新食物的最优求解,利用两个进化因子来加快算法寻优的速度,在观察蜂后期利用混沌算法防止陷入局部最优。根据高校实际排课约束情况,构建数学模型。应用结果表明,混合人工蜂群算法与传统的人工蜂群算法相比,在相同条件下进行自动排课测试,HABC算法在寻优性能和收敛速度上都有显著的优势。

In order to solve the problem that artificial bee colony algorithm cannot break out of local optimain course scheduling,a hybrid artificial bee colony algorithm based on chaos algo-rithm(HABC algorithm)is proposed.The HABC algorithm attaches great importance to the in-fluence of food sources on the bec colony during thc optimization process,increases the optimal solution for new food in adjacent areas,uses two evolutionary factors to accelerate the algo-rithm's optimization speed,and uses chaotic algorithms to prevent falling into local optima in the later stage of observing bees.Construct a mathematical model based on the actual scheduling constraints of universities.The application results show that compared with traditional artificial bee colony algorithms,the hybrid artificial bee colony algorithm has significant advantages in optimization performance and convergence sped when conducting automatic scheduling tests under the same conditions.