王莉1, 3,
唐菱1, 3
1.中国民航大学计算机科学与技术学院 ??天津 ??300300
2.中山大学机器智能与先进计算教育部重点实验室 ??广州 ??510275
3.中国民航大学信息技术科研基地 ??天津 ??300300
4.民航旅客服务智能化应用技术重点实验室 ??天津 ??300300
基金项目:国家自然科学基金(61502499)，中国民航科技创新引导基金项目重大专项(MHRD20140105)，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)，民航旅客服务智能化应用技术重点实验室项目
详细信息
作者简介:卢敏：男，1985年生，讲师，研究方向为机器学习、凸优化
王莉：女，1994年生，硕士生，研究方向为智能信息处理
唐菱：女，1994年生，硕士生，研究方向为数据挖掘
通讯作者:卢敏 lumin@mail.nankai.edu.cn
中图分类号:TP311计量
文章访问数:1088
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被引次数:0
出版历程
收稿日期:2018-02-09
修回日期:2018-07-05
网络出版日期:2018-07-27
刊出日期:2018-10-01
Scheduling Service Staffs for Alien Airlines Using Block Gibbs Sampling
Min LU1, 2, 3, 4,,,Li WANG1, 3,
Ling TANG1, 3
1. College of Computer Science and Technology, Civil Aviation University of China, Tianjin 300300, China
2. Key Laboratory of Machine Intelligence and Advanced Computing, Sun Yat-sen University, Guangzhou 510275, China
3. Information Technology Research Base of CAAC, Civil Aviation University of China, Tianjin 300300, China
4. Key Laboratory of Intelligent Application Technology for Civil Aviation Passenger Services, Tianjin 300300, China
Funds:The National Natural Science Foundation of China (61502499), The Civil Aviation Key Technologies R&D Program of China (MHRD20140105), The Open Project in Key Laboratory of Machine Intelligence and Advanced Computing of the Ministry of Education (Sun Yat-sen University) (MSC-201704A), The Fundamental Research Funds for the Central Universities of China (3122013C005), The Project from Key Laboratory of Intelligent Application Technology for Civil Aviation Passenger Services
摘要
摘要:航空公司外航服务人员排班旨在优化员工排班方案以满足外航航班的人员资质需求，并最小化员工总工作时长和兼顾工作时间均衡，其本质是一个面向多任务类型、员工层次资质、白夜班轮换等约束的人员排班问题。现有算法未考虑白夜班轮换强制性约束，制约了它们的应用。为此，该文提出基于Block Gibbs的航空公司外航服务人员排班算法。算法首先设计了数据拷贝技巧以快速建模具有白夜晚班约束的排班问题，然后提出基于Block Gibbs的多员工有放回抽样优化策略。理论分析表明该文算法与基准算法具有同规模的计算复杂度，但却具有更高的抽样效率以加大可行解生成规模和求解速度。与此同时，在国内某大型航空公司外航服务部排班数据集上的实验表明：相比于基准算法，算法在工作总时长、有效工作时长、有效工作时长比例等指标上提升至少0.62%。
关键词:航班地勤/
人员排班/
吉布斯采样/
层次资质
Abstract:Scheduling staffs servicing alien airlines aims to yield task-person assignments by covering the required skills and minimizing employee total working hours as well as balancing staffs’ workload. Its essence is a personnel scheduling problem constrained by multiple task types, hierarchical skills as well as day and night alternation. The existing algorithms do not consider the constraint of day and night alternation. An algorithm is proposed to address that issue. The proposed algorithm firstly designs a data copy trick to quickly model the issue of staff scheduling constrained by day and night alternation. A novel Block Gibbs sampling technique with replacement is designed to efficiently optimize the formulated problem. Theoretical analysis indicates that the computational complexity of the proposed algorithm is the same scale to that of the baselines, whereas the proposed algorithm gains high sampling efficiency. Experimental results on a real dataset shows the improvement of the proposed algorithm over the existing methods is at least 0.62% in terms of evaluation measures.
Key words:Aircraft ground handling/
Staff scheduling/
Block Gibbs sampling/
Hierarchical skill
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