枢纽机场道面除冰雪机群资源优化配置  

Optimization and allocation research of hub airport pavement fleet deicing resource

作　　者：邢志伟 陈亚雄 罗谦[3] 陈飞[2] 

机构地区：[1]中国民航大学电子信息与自动化学院,成都610041 [2]中国民航大学航空工程学院,天津300300 [3]中国民用航空局第二研究所,成都610041

出　　处：《中国民航大学学报》2017年第6期36-40,51,共6页Journal of Civil Aviation University of China

基　　金：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)

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。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, charac- teristics of airport deicing and fleet operation are analyzed, performance eapaeity-cost multi-objective optimiza- tion 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.

关 键 词：机场道面 除冰雪 机群资源 优化配置 粒子群算法 

分 类 号：V351.11[航空宇航科学与技术—人机与环境工程] TP391[自动化与计算机技术—计算机应用技术]