Modeling resource consumption in the US air transportation system via minimum-cost percolation

Percolation theory has been proven useful to study the robustness of supply-and-demand networks (SDNs) such as transportation and communication infrastructures. Here, we show that it can also be leveraged to understand how resources of SDNs are utilized, and eventually depleted. We introduce a model where rational agents consume network's edges along demanded minimum-cost paths. Due to the finiteness of its resources, the network undergoes a transition between a percolating phase where it can properly serve demand to a non-percolating phase where demand can no longer be supplied. By applying the framework to weighted, directed, temporal, and multi-layer network representations of the US air transportation system, we underscore several key benefits for the overall system that could emerge by simply promoting code-share arrangements among airlines without altering their current schedule of operation. Percolation frameworks have been used to characterize the robustness of infrastructural networks. Here, authors introduce a percolation-based framework to study resource consumption and network effectiveness in meeting the demand.