基于禁忌搜索算法的机场外航服务人员班型生成研究

针对机场外航服务人员班型生成面临的任务量大，约束条件复杂，人工生成班型方案困难等问题背景，考虑员工对任务具有层次资质，班型的各类劳动法规等约束条件，以最小化班型方案总工作时间为优化目标，研究构建了面向多任务层次资质场景下的班型生成优化模型，并设计禁忌搜索算法进行求解。在首都机场外航服务部实际排班数据集上进行实验，验证了模型和算法的实用性和有效性，实验结果表明，求得的班型方案相比较现有人工生成的班型方案，能满足所有约束条件且总工作时间更短，总服务人数更少，提高了机场资源利用率。

Research on Shift Generation of Foreign Airlines Service Personnel Based on Tabu Search Algorithm

To solve the problem for the large amount of tasks, complex constraint conditions and manual which is hard to generation shifts of airport foreign airline service personnel. A shift generation model is studied and constructed for multi-task hierarchical qualification which including employees have hierarchical qualifications for tasks and shift needs to meet all kinds of labor laws and regulations and others constraints to minimize the total working time of shifts for optimum. Tabu search algorithm is designed to solve the model. Experiments, based on the actual scheduling data set of the foreign airlines service department of capital airport, verify the practicability and effectiveness of the model and the algorithm. The results show that compared to the existing manual shifts schemes, shifts obtained by using the model can fulfill all constraint conditions, shorten the total working time, reduce the number of employees and improve the utilization rate of airport resources.