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

Area of Science:

• Network science
• Complex systems
• Transportation engineering

Background:

• Supply-and-demand networks (SDNs) like transportation systems face resource utilization and depletion challenges.
• Percolation theory is established for analyzing SDN robustness but its application to resource dynamics is less explored.

Purpose of the Study:

• To demonstrate percolation theory's utility in understanding resource consumption and depletion in SDNs.
• To model rational agent behavior in consuming network resources along minimum-cost paths.
• To investigate the impact of code-share arrangements on the US air transportation system.

Main Methods:

• Development of a model where agents consume network edges based on minimum-cost paths.
• Analysis of network transitions between percolating (resource-sufficient) and non-percolating (resource-depleted) phases.
• Application of the model to diverse representations of the US air transportation system (weighted, directed, temporal, multi-layer).

Main Results:

• The model reveals a critical transition in network functionality due to finite resource consumption.
• Simulations on the US air transportation system identified potential system-wide benefits from code-share arrangements.
• These benefits can be achieved without altering existing airline schedules.

Conclusions:

• Percolation theory offers a novel framework for analyzing resource dynamics and depletion in complex networks.
• Code-share arrangements represent a strategic intervention to enhance the efficiency and resilience of air transportation networks.
• The study highlights the interconnectedness of resource management and network performance in critical infrastructures.