Analysis of Airline Connectivity using Network Science
DOI:
https://doi.org/10.61841/26jgxj06Keywords:
Graph analytics,, TGO topology, topologyoptimization, NetworkX, pythonAbstract
The airline industry is quite booming nowadays, as the need for faster connectivity increases day by day, Challenges faced by the airline industry are familiar and persistent—Cyclical nature of business, slowing down of global economy, uncertainty of fuel prices, technology, crew cost, Environment, and slow pace of liberalization. India has been projected to be the second-fastest-growing country in the world for passenger traffic by the Airports Council International (ACI) in its traffic forecasts between 2017-40. This industry needs to be consistently profitable, this can be achieved by increasing the connectivity by adopting the concepts of graph theory. The stockpile is converted into a graph by representing all the airports as vertices, and the route between them as edges. This could be consummated by using python as the scripting language and NetworkX package for creating and visualizing graphs. This paper reflects that our proposed model comes with higher performance and less maintenance when compared to the other existing decision-making models.
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