[HTML][HTML] Applications of stochastic modeling in air traffic management: Methods, challenges and opportunities for solving air traffic problems under uncertainty
R Shone, K Glazebrook, KG Zografos - European Journal of Operational …, 2021 - Elsevier
In this paper we provide a wide-ranging review of the literature on stochastic modeling
applications within aviation, with a particular focus on problems involving demand and …
applications within aviation, with a particular focus on problems involving demand and …
Optimized scenario reduction: Solving large-scale stochastic programs with quality guarantees
Stochastic programming involves large-scale optimization with exponentially many
scenarios. This paper proposes an optimization-based scenario reduction approach to …
scenarios. This paper proposes an optimization-based scenario reduction approach to …
Resilient NdFeB magnet recycling under the impacts of COVID-19 pandemic: Stochastic programming and Benders decomposition
Abstract Neodymium-iron-boron (NdFeB) magnets are the most powerful magnets per unit
volume sold in the commercial market. Despite the increasing demand for clean energy …
volume sold in the commercial market. Despite the increasing demand for clean energy …
A configuration optimization approach for reconfigurable manufacturing system based on column-generation combined with graph neural network
F Cui, Z Jiang, X Zhou, J Zheng… - International Journal of …, 2024 - Taylor & Francis
Reconfigurable manufacturing systems (RMS) offer the potential to improve systemic
responsiveness and flexibility to better cope with dynamic environments. However, the …
responsiveness and flexibility to better cope with dynamic environments. However, the …
[HTML][HTML] Conceptualizing UAM: Technologies and Methods for Safe and Efficient Urban Air Transportation
L Zewde, IA Raptis - Green Energy and Intelligent Transportation, 2025 - Elsevier
The effective integration of Urban Air Mobility (UAM) hinges upon the adoption of a
comprehensive approach that harmoniously melds various network components, placing …
comprehensive approach that harmoniously melds various network components, placing …
A probabilistic model based optimization for aircraft scheduling in terminal area under uncertainty
Y Huo, D Delahaye, M Sbihi - Transportation Research Part C: Emerging …, 2021 - Elsevier
Air traffic management relies strongly on the accuracy of prediction, while uncertainties such
as weather, navigation accuracy, pilot operations, etc. may weaken the performance of …
as weather, navigation accuracy, pilot operations, etc. may weaken the performance of …
Predictive and prescriptive analytics for robust airport gate assignment planning in airside operations under uncertainty
With the increasing demand for air transport, numerous airports have exceeded their
available capacity, resulting in more frequent congestion and disruptions. Therefore, airport …
available capacity, resulting in more frequent congestion and disruptions. Therefore, airport …
Machine learning-enhanced aircraft landing scheduling under uncertainties
Aircraft delays lead to safety concerns and financial losses, which can propagate for several
hours during extreme scenarios. Developing an efficient landing scheduling method is one …
hours during extreme scenarios. Developing an efficient landing scheduling method is one …
Primal decomposition for berth planning under uncertainty
Berth planning is an important decision in port operations. The uncertainties in maritime
transportation may result in uncertain ship arrival and service times at a port for every week …
transportation may result in uncertain ship arrival and service times at a port for every week …
Aircraft landing planning under uncertain conditions
Abstract Aircraft Landing Planning is challenging because the inherently limited capacity of
airport runways causes bottlenecks. This type of planning involves different stakeholders …
airport runways causes bottlenecks. This type of planning involves different stakeholders …