中国民航大学学报

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枢纽机场道面除冰雪机群资源优化配置

邢志伟1a,陈亚雄1b,罗谦2,陈飞1b   

  1. (1.中国民航大学 a.电子信息与自动化学院;b.航空工程学院,天津 300300;2.中国民用航空局第二研究所,成都 610041)
  • 收稿日期:2016-05-24 修回日期:2016-09-10 出版日期:2017-12-27 发布日期:2017-12-15
  • 作者简介:邢志伟(1970—),男,辽宁新民人,研究员,博士,主要研究方向为民航装备与系统、民航智能规划与调度.
  • 基金资助:
    国家自然科学基金项目(U1533203);中央高校基本科研业务费专项(3122014P003)

Optimization and allocation research of hub airport pavement fleet deicing resource

XING Zhiwei1a, CHEN Yaxiong1b, LUO Qian2, CHEN Fei1b   

  1. (1a. College of Electronic Information and Automation; 1b. College of Aeronautical Engineering, CAUC, Tianjin 300300, China;
    2. Second Institute of CAAC, Chengdu 610041, China)
  • Received:2016-05-24 Revised:2016-09-10 Online:2017-12-27 Published:2017-12-15

摘要: 机场除冰雪效率对机场运营质量以及航班正点率影响深远,针对机场道面除冰雪机群资源优化配置问题,分析了机场道面除冰雪以及机群作业特性,建立了基于作业能力-成本的多目标机场道面除冰雪机群资源优化配置模型,改进了标准粒子群算法来求解模型。以国内某大型枢纽机场跑道除冰雪为例,对模型进行了仿真分析,得到了不同雪情条件下的机群资源优化配置结果并与经验配置方式对比。结果表明,模型配置方式在作业效率与成本方面均优于经验配置方式。

关键词: 机场道面, 除冰雪, 机群资源, 优化配置, 粒子群算法

Abstract: The airport deicing rate has far-reaching influence on airport operating quality as well as flight punctuality rate.In view of the problem about fleet resource optimization and allocation for hub airport pavement deicing, characteristics of airport deicing and fleet operation are analyzed, performance capacity-cost multi-objective optimization and allocation model about airport deicing is built, standard article swarm algorithm is improved to solve the model. Based on the deicing case of a large hub airport, the model is simulated and analysed, the fleet resource optimization and configuration results are obtained under different snow conditions. Results show that the model configuration mode is superior to the experience configuration mode in operation efficiency and cost.

Key words: airport pavement, deicing, fleet resource, optimization and allocation, article swarm algorithm

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