摘要
针对大型枢纽机场面临的航班行李分拣站分配任务越来越繁重、约束条件复杂、优化困难等问题,分析了旅客行李处理流程并给出了机场航班行李分拣站分配问题的形式化描述,提出了面向机场不同业务需求的行李分拣站分配方案性能评价指标。以均衡度最小、偏好匹配度最大和空闲行李分拣站数量最大为优化目标,研究构建了行李分拣站分配问题多目标优化模型,并设计了遗传算法求解该模型。基于北京首都国际机场实际运行数据的仿真验证表明,提出的分配方案在各个评价指标上均有较好表现,相较于机场现行方案,有显著优势,能很好地满足机场实际的运行需求。
Aiming at the problems of increasing assignment of baggage sorting station to flights, complex constraints, and difficulties in optimization for large hub airports, the business process of airport baggage handling was analyzed, the baggage sorting station allocation problem was described formally and three different performance evaluation indexes were proposed for different business requirements. Regard the equilibrium degree, the preference matching degree and the free baggage sorting station number as the optimization objectives, a multi-objective optimization model for the baggage sorting allocation was constructed, and the genetic algorithm was designed to solve the model. The simulation experiments based on the actual operation data of Beijing Capital International Airport show that the allocation strategy proposed in this paper performs better in each index than the current allocation strategy in the airport, and can satisfy the operation requirements of the airport.
作者
左海超
蔡翔
冯霞
ZUO Hai-chao;CAI Xiang;FENG Xia(Information Technology Research Base of Civil Aviation Administration of China,Civil Aviation University of China,Tianjin 300300,China;College of Computer Science and Technology,Civil Aviation University of China,Tianjin 300300,China)
出处
《计算机仿真》
北大核心
2018年第9期52-58,共7页
Computer Simulation
基金
中国民航科技创新引导资金项目重大专项(MHRD20140105)
中央高校科研业务费专项资金(3122015z007)
关键词
行李分拣站
性能指标
多目标优化
均衡度
偏好匹配度
遗传算法
Baggage sorting station
Performance evaluation index
Multi-objective optimization
Equilibrium degree
Preference matching degree
Genetic algorithm
