A network science approach to identify disruptive elements of an airline
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Nowadays, flight delays are quite notorious and propagate from an originating flight to connecting flights, which lead to big disruptions in the overall schedule. These disruptions cause huge economic losses, affect the reputation of airlines, lead to a wastage of time and money of passengers, and have a direct environmental impact. This paper presents a novel network science approach for modelling and analysis of an airline's flight schedules and its historical operational data. The final aim is to find out the most disruptive airports, flights, flight-connections and connection-type in an airline network. In this regard, disruptive elements refer to influential or critical entities of an airline network. These are the elements which either can cause (as per airline schedules) or has caused (as per the historical data) the biggest disturbances in the network. An airline, then can improve their operations by avoiding disruptive elements. This can be achieved through introduction of an extra slack time between connecting flights and by creation of alternate arrangements for aircraft and crew members for the disruptive flights and flight-connections. The proposed network science approach for disruptive elements' analysis is validated with a case-study of an operating airline. Interestingly, the analysis shows that (potential) disruptive elements in the schedule of the airline are also (actual) disruptive elements in the historical data and should be attended first to improve operations.
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