摘要
面向班型动态生成的地服人员排班旨在动态生成班型,并将员工分配到班型中,以班型为航班地面保障单元.现有面向班型的人员排班算法是建立在固定班型数和班型内的员工资质数,未考虑班型数未知的重要前提.为此,提出面向班型动态生成的地服人员排班算法,其核心思想是通过block Gibbs抽样迭代优化班型内人员构成、班型内航班集和班型生成.在某机场值机人员的数据集中验证此算法,实验结果表明,在满足员工层次资质、员工白夜班和班型动态生成的约束下,算法能够生成合理的班型.
The problem of scheduling airport ground staffs is to dynamically generate groups and assign employees to groups.The existing group-specific staff scheduling algorithms are built on the fixed number of groups.Nevertheless,it is impractical to know the number of groups in advance.An algorithm is proposed to address the issue via dynamically generating groups.Its key idea is to employ Gibbs sampling with replacement to iteratively optimize three sub-problems:assigning staffs to groups,allocating flights to groups and group generation.Experimental results on a real dataset demonstrate that the proposed algorithm can generate reasonable groups under the constraints of skill requirements for flights and shifts for employees.
作者
卢敏
王莉
LU Min;WANG Li(Information Technology Research Base of CAUA,Civil Aviation University of China,Tianjin 300300,China;College of Computer Science and Technology,Civil Aviation University of China,Tianjin 300300,China;Key Laboratory of Machine Intelligence and Advanced Computing,Ministry of Education,Sun Yat-sen University,Guangzhou 510275,China)
出处
《交通运输系统工程与信息》
EI
CSCD
北大核心
2018年第4期54-60,共7页
Journal of Transportation Systems Engineering and Information Technology
基金
国家自然科学基金(61502499)
中山大学机器智能与先进计算教育部重点实验室开放课题(MSC-201704A)
中央高校基本科研业务费科研专项(3122013C005)~~
关键词
航空运输
班型动态生成
吉布斯采样
人员排班
air transportation
dynamic group generation
Gibbs sampling
staffs scheduling
