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An optimization model to assign seats in long distance trains to minimize SARS-CoV-2 diffusion

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  • Haque, Md Tabish
  • Hamid, Faiz

Abstract

The unprecedented spread of SARS-CoV-2 has pushed governmental bodies to undertake stringent actions like travel regulations, localized curfews, curb activity participation, etc. These restrictions assisted in controlling the proliferation of the virus; however, they severely affected major economies. This compels policymakers and planners to devise strategies that restrain virus spread as well as operationalize economic activities. In this context, we discuss some of the potential implications of seat inventory management in long-distance passenger trains and create a balance between operators’ operational efficiency and passengers’ safety. The paper introduces a novel seat assignment policy that aims to mitigate virus diffusion risk among passengers by reducing interaction among them. A mixed-integer linear programming problem has been formulated that concomitantly maximizes the operator’s revenue and minimizes virus diffusion. The validity of the model has been tested using real-life data obtained from Indian Railways. The computational results show that a mere 50% capacity utilization may distress operators’ economics and prove ineffectual in controlling SARS-CoV-2 transmission. The proposed model produces encouraging results in restricting virus diffusion and improving revenue even under 100% capacity utilization.

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  • Haque, Md Tabish & Hamid, Faiz, 2022. "An optimization model to assign seats in long distance trains to minimize SARS-CoV-2 diffusion," Transportation Research Part A: Policy and Practice, Elsevier, vol. 162(C), pages 104-120.
    • Handle: RePEc:eee:transa:v:162:y:2022:i:c:p:104-120
    DOI: 10.1016/j.tra.2022.05.005
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    1. A. Ciancimino & G. Inzerillo & S. Lucidi & L. Palagi, 1999. "A Mathematical Programming Approach for the Solution of the Railway Yield Management Problem," Transportation Science, INFORMS, vol. 33(2), pages 168-181, May.
    2. Jin Qin & Yijia Zeng & Xia Yang & Yuxin He & Xuanke Wu & Wenxuan Qu, 2019. "Time-Dependent Pricing for High-Speed Railway in China Based on Revenue Management," Sustainability, MDPI, vol. 11(16), pages 1-18, August.
    3. Raja Gopalakrishnan & Narayan Rangaraj, 2010. "Capacity Management on Long-Distance Passenger Trains of Indian Railways," Interfaces, INFORMS, vol. 40(4), pages 291-302, August.
    4. Alexander Armstrong & Joern Meissner, 2010. "Railway Revenue Management: Overview and Models (Operations Research)," Working Papers MRG/0019, Department of Management Science, Lancaster University, revised Jul 2010.
    5. Michael F. Gorman, 2015. "Operations Research in Rail Pricing and Revenue Management," International Series in Operations Research & Management Science, in: Bruce W. Patty (ed.), Handbook of Operations Research Applications at Railroads, edition 127, chapter 0, pages 243-254, Springer.
    6. Wuyang Yuan & Lei Nie & Xin Wu & Huiling Fu, 2018. "A dynamic bid price approach for the seat inventory control problem in railway networks with consideration of passenger transfer," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-23, August.
    7. Pierre Nouvellet & Sangeeta Bhatia & Anne Cori & Kylie E. C. Ainslie & Marc Baguelin & Samir Bhatt & Adhiratha Boonyasiri & Nicholas F. Brazeau & Lorenzo Cattarino & Laura V. Cooper & Helen Coupland &, 2021. "Reduction in mobility and COVID-19 transmission," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
    8. Strauss, Arne K. & Klein, Robert & Steinhardt, Claudius, 2018. "A review of choice-based revenue management: Theory and methods," European Journal of Operational Research, Elsevier, vol. 271(2), pages 375-387.
    9. Wang, Xinchang & Wang, Hua & Zhang, Xiaoning, 2016. "Stochastic seat allocation models for passenger rail transportation under customer choice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 96(C), pages 95-112.
    10. Bharill, Rohit & Rangaraj, Narayan, 2008. "Revenue management in railway operations: A study of the Rajdhani Express, Indian Railways," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(9), pages 1195-1207, November.
    11. Michael Schultz & Jörg Fuchte, 2020. "Evaluation of Aircraft Boarding Scenarios Considering Reduced Transmissions Risks," Sustainability, MDPI, vol. 12(13), pages 1-20, July.
    12. Klein, Robert & Koch, Sebastian & Steinhardt, Claudius & Strauss, Arne K., 2020. "A review of revenue management: Recent generalizations and advances in industry applications," European Journal of Operational Research, Elsevier, vol. 284(2), pages 397-412.
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    1. Haque, Md Tabish & Hamid, Faiz, 2023. "Social distancing and revenue management—A post-pandemic adaptation for railways," Omega, Elsevier, vol. 114(C).

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