Coordinated aviation network resource allocation under uncertainty

Congestion in the air traffic system, both recurrent and non-recurrent, is typically handled by rationing access rights to individual resources such as airports or important parts of the airspace. Under the planning paradigm employed in the US, this rationing process occurs independently at each resource. The stochastic integer programming model proposed in this paper brings coordination to this process while considering capacity uncertainty. Results of a case study suggest that the model is tractable, and generates capacity allocations that improve efficiency and enable greater responsiveness to changing capacity conditions.

► This paper considers coordination of air traffic flow management initiatives under capacity uncertainty.
► Two stage stochastic optimization model is proposed.
► Case study demonstrates model utility and tractability.