期刊文献+

基于改进NSGA-Ⅱ的停机位预分配优化

Optimization of Gate Pre‑allocation Based on Improved NSGA‑Ⅱ
下载PDF
导出
摘要 随着民航运输业的发展,航班密度不断增加,大型机场的近机位资源紧张问题日益突出,降低了航班保障效率。为了探索大型枢纽机场停机位预分配问题综合有效的解决方法,从航空公司、机场和旅客的实际情况出发,建立多目标停机位分配优化模型,并设计了改进的带精英策略的非支配排序遗传算法(Non-dominated sorting genetic algorithms-Ⅱ,NSGA-Ⅱ)对模型进行求解,得到一组Pareto前沿解。。在交叉和变异操作阶段,对种群个体以指数形式自适应地调整交叉率和变异率,以此提高算法的收敛速度和优良解的多样性。实例验证结果表明,该模型和改进算法相较于人工分配和传统NSGA-Ⅱ算法对停机位指派的优化结果更为突出,尤其在靠桥率和被使用的停机位数量方面;同时利用性能评价指标对比两种算法,发现改进型NSGA-Ⅱ算法更适合停机位预分配问题的求解。 With the development of the civil aviation transportation industry,the density of flights is increasing,and the shortage of near-airport resources in large airports has become increasingly prominent.The lack of near⁃airport resources reduces the efficiency of flight guarantees.In order to develop a comprehensive and effective solution to the problem of gate pre⁃allocation in large hub airports,based on the actual situation of airlines,airports and passengers,a multi⁃objective parking space allocation optimization model is established,and an improved non⁃dominated sorting genetic algorithm(NSGA⁃Ⅱ)with an elite strategy is designed to solve the model.The Pareto frontier solution is obtained.In the crossover and mutation operation stage,the crossover rate and the mutation rate are adaptively adjusted for the population individuals in an exponential form,so as to improve the convergence speed of the algorithm and the diversity of excellent solutions.The example verification results show that the optimization results of the model and the improved algorithm are more prominent than the manual allocation and the traditional NSGA⁃Ⅱalgorithm for parking space assignment,especially in terms of the bridge rate and the number of used parking stands.At the same time,the performance evaluation index is used to compare the two algorithms,and found that the improved NSGA⁃Ⅱalgorithm is more suitable for solving the gate pre⁃allocation problem.
作者 刘禹汐 刘继新 田文 LIU Yuxi;LIU Jixin;TIAN Wen(College of Civil Aviation,Nanjing University of Aeronautics&Astronautics,Nanjing 211106,China;National Key Laboratory of Air Traffic Flow Management,Nanjing 211106,China)
出处 《南京航空航天大学学报》 CAS CSCD 北大核心 2023年第2期329-338,共10页 Journal of Nanjing University of Aeronautics & Astronautics
基金 国家重点研发计划(2021YFB1600500) 国家自然科学基金(71971112) 南京航空航天大学科研与实践创新计划(xcxjh20220709)。
关键词 停机位预分配 多目标优化 改进型NSGA-Ⅱ Pareto前沿解 性能评价指标 gate pre⁃allocation multi⁃objective optimization improved NSGA⁃Ⅱ Pareto frontier solution performance evaluation indicators
  • 相关文献

参考文献11

二级参考文献65

  • 1杨守剑,白存儒.机场停机位优化分配研究[J].航空工程进展,2010,1(3):301-305. 被引量:3
  • 2王志清,欧阳杰,宁宣熙.航空运输便捷性问题优化研究[J].管理世界,2006,22(6):147-148. 被引量:2
  • 3常钢,魏生民.基于组合优化的停机位分配模型研究[J].中国民航学院学报,2006,24(3):28-31. 被引量:4
  • 4陈欣,陆迅,朱金福.机场停机位指派模型及算法[J].交通运输工程学报,2006,6(4):88-90. 被引量:8
  • 5McLay P. Aisling reynolds feighan,competition between airport terminals:the issues facing dublin airport[J], Transportation Research Part A: Policy and Practice ,2006,40(2) : 181-203.
  • 6亚历山大 T.韦尔斯.机场规划与管理[M].赵宏元译.北京:中国民航出版社,2004.150.
  • 7Su Y Y,Srihari K. A knowledge-based aircraft gate assignment advisor[J]. Computers and Industrial Engineering, 1993,25 (2) : 123-126.
  • 8Bihr R. A conceptual solution to the aircraft gate assignment problem using 0,1 linear programming[J] Computers and Industrial Engineering,1990,19(3):280-284.
  • 9YAN S, HUO C. Optimization of multiple objective gate assignments [J]. Transportation Research A, 2001 (35) : 413-432.
  • 10YAN Shangyao, SHIEH Chiyuan,CHEN Miawjane. A simulation framework for evaluating airport gate assignments EJ3. Transportation Research Part A,2002(36):885-898.

共引文献61

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部