基于遗传算法的加油车和摆渡车协同调度研究

交通运输系统工程与信息 ›› 2016, Vol. 16 ›› Issue (2): 155-163.

基于遗传算法的加油车和摆渡车协同调度研究

冯霞*^1,2，任子云¹

1. 中国民航大学计算机科学与技术学院, 天津300300；2. 中国民航信息技术科研基地, 天津300300

收稿日期:2015-07-21 修回日期:2015-11-25 出版日期:2016-04-25 发布日期:2016-04-25
作者简介:冯霞(1970-)，女，天津人，教授，博士.
基金资助:
国家自然科学基金资助项目/National Natural Science Foundation of China（61502499）；中国民航科技创新引导资金项目重大专项/ Civil Aviation Key Technologies R&D Program of China（MHRD20140105）；中央高校科研业务费专项资金/ Fundamental Research Funds for the Central Universities（3122013C005，3122014D032，3122015D015）；中国民航大学科研基金项目/ Scientific Research Foundation from Civil Aviation University of China（2013QD18X）；中国民航信息技术科研基地开放课题基金项目/ The Open Project Foundation of Information Technology Research Base of Civil Aviation Administration of China（CAAC-ITRB-201401）.

Collaborative Scheduling of Fuelling Vehicle and Ferry Vehicle Based on Genetic Algorithm

FENG Xia^1,2, REN Zi-yun¹

1. College of Computer Science and Technology, Civil Aviation University of China, Tianjin 300300, China； 2. Information Technology Research Base of CAAC, Tianjin 300300, China

Received:2015-07-21 Revised:2015-11-25 Online:2016-04-25 Published:2016-04-25

摘要/Abstract

摘要：

航班地面服务是机场运行的重要环节.航班在机场过站期间所接受的一系列地面服务通过不同类型的保障车辆来执行.通过分析机场过站航班保障的业务流程，确定了加油服务和上客服务的时间约束关系，并在此基础上，以至少需要的保障车辆数目和服务总开始时间最早为目标，研究构建了远机位航班加油服务和上客服务的协同调度模型，并给出了基于多目标遗传算法的模型求解.基于首都国际机场实际运行数据的实验结果表明，所提出的模型能较好地解决加油车和摆渡车协同调度问题.实验得到一组Pareto 最优解为业务部门提供决策支持.

关键词: 航空运输, 协同调度, 遗传算法, 保障车辆, 多目标优化, 航班地面服务调度

Abstract:

Aircraft ground service is an important part of the airport operation. The series of ground services aircraft accepts during its turnaround time are performed by non- homogeneous service vehicles. Time constraint relationship between refueling services and boarding services is determined through analyzing operational process of airport flight turnaround services. Then collaborative scheduling model of refueling services and boarding services of the apron flights is built. The collaborative scheduling model has two objectives. One is minimizing the total number of fuelling vehicle and ferry vehicle the services need. The other is minimizing the total start time of refueling services and boarding services. Then the solution method for the model based on multi- objective genetic algorithm is given. Experimental results based on actual operation data of Beijing Capital International Airport show that the proposed model could solve the collaborative scheduling problem of fuelling vehicle and ferry vehicle well. A set of Pareto optimal solutions obtained from the experiment could provide decision support for business departments.

Key words: air transportation, collaborative scheduling, genetic algorithm, service vehicles, multiobjective optimization, aircraft ground service scheduling

中图分类号:

V351
O224

冯霞，任子云. 基于遗传算法的加油车和摆渡车协同调度研究[J]. 交通运输系统工程与信息, 2016, 16(2): 155-163.

FENG Xia, REN Zi-yun. Collaborative Scheduling of Fuelling Vehicle and Ferry Vehicle Based on Genetic Algorithm[J]. Journal of Transportation Systems Engineering and Information Technology, 2016, 16(2): 155-163.

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链接本文: http://www.tseit.org.cn/CN/abstract/abstract19171.shtml

http://www.tseit.org.cn/CN/Y2016/V16/I2/155

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