A Network Science-Based Performance Improvement Model for the Airline Industry Using NetworkX

Author(s): Vishnu Vardhan Reddy Kollu, Shanmuk Srinivas Amiripalli*, Mukkamala Siva Naga Ventaka Jitendra, Tirandasu Ravi Kumar

Journal Name: International Journal of Sensors, Wireless Communications and Control

Volume 11 , Issue 7 , 2021


Become EABM
Become Reviewer
Call for Editor

Graphical Abstract:


Abstract:

Background: COVID 19 created a challenging situation for many of the industries across the globe. Our primary focus is on the most affected airline industry. In this paper, the connectivity and profits of an airline company were analyzed with the theoretical approach and by proposing a novel model to increase the performance of the above parameters. In our previous work, two airlines were investigated, and it was observed that adding trips to a non-profit airline concerning profit Airlines is one of the optimal techniques to improve the performance. In this paper, multi-airlines have been considered.

Methods: In the first step, identify the appropriate data sets for three airline companies and the collected data set in image format, to convert them into graph format consisting of nodes and edges. In the next step, an analysis has been conducted on data set graphs by considering the parameters like diameter, density, average degree, clustering coefficient and the shortest path generated to identify the profitable airlines. The proposed algorithms will apply either trimming or adding operations on lowprofit airline operators with respective profitable airlines. In the last step, the proposed algorithm will generate an output with better connectivity and profits.

Results: In this research, other interesting findings, which are relatively contrasted to the previous findings, were observed. In the present research findings, trimming of trips to non-profit airlines concerning the profit airlines can also be an optimal solution for better performance.

Discussion: In this research, complex multigraph airlines were analyzed by using the graph analytics technique for the optimum solution. Standard parameters like edges, nodes, degree, clustering, and shortest path on indigo, spice jet, and AirAsia airline systems were also compared.

Conclusion: The proposed algorithm analyzes the connectivity of airline systems and applies either trimming or enhancing techniques. Indigo airlines have the best-connected network as compared to the other two models. Trimming operations will be performed on Indigo, whereas on Air Asia and spice jet, both cutting and enhancing will be served.

Keywords: Graph analytics, TGO topology, topology optimization, NetworkX, python, airlines.

Rights & PermissionsPrintExport Cite as

Article Details

VOLUME: 11
ISSUE: 7
Year: 2021
Published on: 29 October, 2020
Page: [768 - 773]
Pages: 6
DOI: 10.2174/2210327910999201029194155
Price: $25

Article Metrics

PDF: 202