摘要
为解决机场和定位点动态容量条件下的航班进离场流量优化分配问题,以总航班延误损失为决策依据,建立了绝对鲁棒优化模型、偏差鲁棒优化模型和相对鲁棒优化模型,并用捕食搜索算法,设计了寻找鲁棒最优解的算法流程.以国内某机场数据为例进行仿真验证,结果表明,得到的鲁棒最优解能够根据不同偏好有效规避风险,与该终端区一般容量条件下最优解的航班延误损失相比,偏差鲁棒最优策略和相对鲁棒最优策略下的航班延误损失分别减少了8.2%和7.8%.
To optimize the allocation of aircraft arrival and departure flow under dynamic capacity of airports and fixes,an absolute robust optimization model,a deviation robust optimization model,and a relative robust optimization model were built,where the objective function is to minimize the total cost of delayed flights.Then,a solution process based on predatory search algorithm was developed to solve the robust optimization problems.A case study regarding the operation of one of Chinese airports was performed to verify the models.The simulation results show that the robust optimal solutions produced from these models could effectively avoid risks on the basis of different decision preferences in actual operations;compared with the optimal solution under the capacity of terminal area with common conditions,the strategy of deviation robust optimization could reduce the delay cost by 8.2%,and the strategy of relative robust optimization could reduce the delay cost by 7.8%.
出处
《西南交通大学学报》
EI
CSCD
北大核心
2010年第2期261-267,共7页
Journal of Southwest Jiaotong University
基金
国家863计划重点项目(2006AA12A105)
关键词
空中交通管理
流量分配
鲁棒优化
捕食搜索算法
动态容量
air traffic management
flow allocation
robust optimization
predatory search algorithm
dynamic capacity
