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作 者:徐涛[1,2,3] 吴志帅 卢敏 吕宗磊[1,2,3] 李忠虎 XU Tao;WU Zhishuai;LU Min;LYU Zonglei;LI Zhonghu(College of Computer Science and Technology, Civil Aviation University of China, Tianjin 300300, China;Civil Aviation Information Technology Research Base, Civil Aviation University of China, Tianjin 300300, China;Key Laboratory of Intelligent Application Technology for Civil Aviation Passenger Service, Beijing 101318, China)
机构地区:[1]中国民航大学计算机科学与技术学院,天津300300 [2]中国民航大学民航信息技术科研基地,天津300300 [3]民航旅客服务智能化应用技术重点实验室,北京101318
出 处:《系统工程与电子技术》2020年第11期2553-2559,共7页Systems Engineering and Electronics
基 金:国家自然科学基金项目(61502499);天津市自然科学基金(18JCYBJC85100);教育部人文社会科学研究规划基金项目(19YJA630046)资助课题。
摘 要:为解决枢纽机场客流拥堵问题,提高机场运行效率,减少运营成本,提出了一种面向拥堵问题的枢纽航线网络优化模型。该模型基于非严格枢纽航线网络结构,以不同运输方式的费用和流量为约束条件,以枢纽航线网络成本最低为目标,设计了能够减少求解运算的复杂变量表示方法,以及减少陷入局部最优解概率的模拟退火粒子群优化(simulated annealing particle swarm optimization,SAPSO)算法。实验结果表明,相较于严格的枢纽航线网络,所提优化模型能够显著地缓解枢纽机场的拥堵,均衡枢纽机场间客流量,减少网络成本;同时,所提算法具有较快的收敛速度和良好的稳定性。In order to solve the problem of passenger flow congestion at the hub airport,improve airport operation efficiency,and reduce operating costs,an optimization model of the hub-and-spoke network for congestion problem is proposed.The model is based on the structure of non-strict hub-and-spoke network,with costs and flows of different modes of transportation as constraints,and the goal of minimizing the hub-and-spoke network costs.A complex variable representation method that can reduce the calculation and the simulated annealing particle swarm optimization(SAPSO)algorithm,which can reduce the probability of falling into a local optimal solution is designed.The experimental results show that compared with the strict hub-and-spoke network,the optimization model proposed can significantly alleviate the congestion of the hub airport,balance passnger flow between hub airports and reduce the network cost.At the same time,the proposed algorithm has faster convergence speed and better stability.
关 键 词:航空运输 枢纽航线网络 模拟退火粒子群优化算法 拥堵问题 直航
分 类 号:TP301.6[自动化与计算机技术—计算机系统结构]
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