Using Markov decision processes to solve stochastic gate assignment problem

Oussama Aoun, A. E. Afia
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引用次数: 10

Abstract

Airport traffic often undergoes some random disruptions, which have to be considered to ensure operational flight-gate assignments. Inadequate assignment of gates may result in flight delays that happen in airport operations and must be taken into account. Here, we are using the original algorithm, based on Markov decision process (MDP) to solve the gate assignment problem (GAP) under uncertainty; we include stochastic parameters that depend on probabilities to express fluctuations in flight operations. The use of MDP for modeling will provide for airport controllers a robust solution for the GAP that takes in consideration possible flight delays. This paper gives the corresponding model, which includes strict constraints of the GAP and other soft constraints like choice preferences of gates. We give experimental results on a sample of real data to demonstrate the feasibility and efficiency of our approach.
用马尔可夫决策过程求解随机门分配问题
机场交通经常会遇到一些随机的中断,必须考虑到这些中断,以确保正常运行的登机门分配。登机口分配不当可能导致机场运营中发生的航班延误,这一点必须加以考虑。在此,我们使用基于马尔可夫决策过程(MDP)的原始算法来解决不确定条件下的门分配问题(GAP);我们包括依赖于概率的随机参数来表示飞行操作中的波动。使用MDP进行建模将为机场管制员提供一个健壮的GAP解决方案,该解决方案考虑了可能的航班延误。本文给出了相应的模型,该模型包含GAP的严格约束和门的选择偏好等软约束。最后给出了实际数据样本的实验结果,验证了该方法的可行性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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