A Study on Decision-Making of the Indian Railways Reservation System during COVID-19

Author:

Sharma Haresh Kumar1ORCID,Majumder Saibal2ORCID,Biswas Arindam3ORCID,Prentkovskis Olegas4ORCID,Kar Samarjit5,Skačkauskas Paulius4ORCID

Affiliation:

1. Department of Mathematics, Shree Guru Gobind Singh Tricentenary University, Gurugram, India

2. Department of Computer Science and Engineering, NSHM Knowledge Campus, Durgapur, India

3. School of Mines and Metallurgy, Kazi Nazrul University (Public University), Asansol, India

4. Department of Mobile Machinery and Railway Transport, Faculty of Transport Engineering, Vilnius Gediminas Technical University, Vilnius, Lithuania

5. Department of Mathematics, National Institute of Technology, Durgapur, India

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.

Publisher

Hindawi Limited

Subject

Strategy and Management,Computer Science Applications,Mechanical Engineering,Economics and Econometrics,Automotive Engineering

Reference28 articles.

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