摘要
机场航班时刻优化是提升机场运行效益的一个重要手段。针对现有研究主要从容流平衡和时刻分配的公平性上来对进离场航班时刻进行分配,但鲜有考虑航班时刻收益这一因素的问题,提出了一种航空公司运行收益最大、航班时刻总偏移量最小和公平性偏差最小的多目标航班时刻优化模型,运用改进的粒子群算法对模型进行求解,并以深圳宝安机场的历史数据验证了模型的有效性。试验结果表明,优化后航空公司整体平均收益相对上升了0.231%,平均公平性偏差系数下降了35.455%,平均时刻调整量下降了11.243%,达到了提高航空公司收益的目的。
Airport flight schedules optimization is a critical strategy for improving airport operational efficiency.In view of the problem that existing research has predominantly focused on the allocation of arrival and departure flight slots,emphasizing congestion equilibrium and fairness in distribution,but seldom consider the factor of the aspect of flight schedule revenue,a multi-objective flight schedule optimization model was proposed,which maximizing operational revenue for airlines while minimizing the overall flight schedule deviation and fairness deviation.An enhanced particle swarm algorithm was applied to solve the proposed model,and its effectiveness was validated using historical data from Shenzhen Bao'an Airport.Test results show that after optimization,the average revenue for airlines has increased by 0.231%,the average fairness deviation coefficient has decreased by 35.455%,and the average schedule adjustment has reduced by 11.243%.These results demonstrate the efficacy of the approach in enhancing airline revenue.
作者
王莉莉
潘越
WANG Lili;PAN Yue(College of Air Traffic Management,Civil Aviation University of China,Tianjin 300300,China)
出处
《飞行力学》
CSCD
北大核心
2024年第2期89-94,共6页
Flight Dynamics
基金
国家自然科学基金委与中国民用航空局联合基金资助(U1633124)。
关键词
空中交通流量管理
帕累托解集
多目标算法
航班时刻优化
air traffic flow management
Pareto solution
multi-objective algorithm
flight schedule optimization
