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A study on decision-making of the Indian Railways Reservation System during COVID-19

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Date
2022
Author
Sharma, Haresh Kumar
Majumder, Saibal
Biswas, Arindam
Prentkovskis, Olegas
Kar, Samarjit
Skačkauskas, Paulius
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Abstract
The Indian Railways Reservation System (IRRS) is one of the world’s busiest reservation systems of railway tickets. Recently, the COVID-19 pandemic situation has severely impacted the Indian Railway’s (IR) transportation, which eventually has enforced the IR to alter the passenger reservation system. This research attempts to evaluate and analyse the factors that modify the IRRS. In this research, a rough set-based Data Mining Scaffolding (DMS) has been proposed. Here, the relevant preferential information related to the IRRS is managed by introducing a multi-criteria decision-making (MCDM), where a decision-maker (DM) can make a decision based on several decision rules. The effectiveness of the proposed DMS is explained by gathering realistic data of 26 trains, which run between railway stations of two metro cities of India during the COVID-19 pandemic period.
Issue date (year)
2022
URI
https://etalpykla.vilniustech.lt/handle/123456789/113133
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  • Straipsniai Web of Science ir/ar Scopus referuojamuose leidiniuose / Articles in Web of Science and/or Scopus indexed sources [7946]

 

 

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