机场客运大楼的随机规划方法

Hesam. Shabani Verki, A. Mamdoohi, M. Saffarzadeh
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引用次数: 2

摘要

针对机场客运站规划面临的挑战,研究了一种基于整个机场客运站多商品流网络表示的多阶段随机规划模型。由于机场航站楼通道和处理站的延误具有不同的不确定性,分别对其进行建模,然后进行整合。在本研究中,我们将机场航站楼容量规划问题作为一个整体来考虑。在这方面,我们首先推导时间函数来近似机场航站楼通道和处理站的最大延误。将需求不确定性视为规划视界内的动态随机数据过程,并将其建模为情景树。基于伊玛目霍梅尼国际机场现有的旅客需求等数据,提出了一种对需求情景有充分追索权的多阶段随机规划模型。数值结果表明,多阶段模型的解远远优于均值确定性模型和三阶段随机模型的最优解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stochastic Planning Approach in Airport Passenger Terminals
Motivated by the challenges encountered in airport passenger terminal planning, we study a multistage stochastic programming model based on a multi commodity flow network representation of the whole airport terminal. As delays in passageways and processing stations of airport terminal different uncertain natures, they are modeled separately and then integrated. In this study, we consider the airport terminal capacity planning problem as a whole. In this regard, we first derive time functions to approximate maximum delays in passageways and processing stations of an airport terminal. Demand uncertainty is considered as a dynamic stochastic data process during the planning horizon which is modeled as a scenario tree. Based on available data for the Imam Khomeini International Airport like passenger demands, a multi-stage stochastic programming model is proposed which is full recourse for demand scenarios. Numerical results indicate that the solution to the multi-stage model is far superior to the optimal solution to the mean-value deterministic and the three-stage stochastic models. 
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