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Optimum transportation of relief materials aftermath the disaster

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Purpose: Natural disasters disrupt not only the lives of individuals but also the functioning of society. Given the unpredictability of disasters and the uncertainty associated with them, preparation is the best way to mitigate and reduce the effects of the disaster. Design/methodology/approach: The study presents a mathematical model in the form of a multi-objective linear programming problem for the relief distribution from the airports which minimizes the total operational cost as well as travel time. Further, the solution approach and analytical results have also been discussed. Findings: The main aims at the preparedness stage are to identify and build infrastructures that might function as useful operation centres during a disaster. The study also provides decisions that include the type and number of vehicles for each affected location. Research limitations/implications: Airports can function as centres for relief collection and distribution. However, relief operations carried out through airports are often subject to problems such as stockpiling. Further, various modes are available for the transport of relief supplies- air, water, and land transport modes primarily. While aircraft and helicopters are faster, their costs of operation are too high. Instead, trucks are economical but very slow as compared to aircraft. Practical implications: The choice of model depends on many factors including the availability of vehicles, availability of routes, and criticality of situations. The choices made in turn affect the costs and the time of operations. Originality/value: The model converts a disaster scenario into a demand-supply problem with the aim being to decide allocations at specified intervals of time.
Rocznik
Strony
26--41
Opis fizyczny
Bibliogr. 32 poz., rys., tab., wykr.
Twórcy
autor
  • Civil Engineering Department, National Institute of Technology Hamirpur, Himachal Pradesh, India
autor
  • Department of Civil Engineering, Chitkara University Institute of Engineering and Technology, Chitkara University, Patiala, Punjab, India
autor
  • Department of Civil Engineering, Shoolini University, Solan, Himachal Pradesh, India
autor
  • Civil Engineering Department, National Institute of Technology Hamirpur, Himachal Pradesh, India
Bibliografia
  • [1] N. Altay, W.G. Green III, OR/MS research in disaster operations management, European Journal of Operational Research 175/1 (2006) 475-493. DOI: https://doi.org/10.1016/j.ejor.2005.05.016
  • [2] X. Bai, Two stage multiobjective optimization for emergency supplies allocation problem under integrated uncertainty. Mathematical Problems in Engineering 2016 (2016) 2823835. DOI: https://doi.org/10.1155/2016/2823835
  • [3] A.K. Jain, A Practical Guide to Disaster Management, Pragun Publications, New Delhi, 2018.
  • [4] BBC news, Nepal earthquake: Eight million people affected, UN says. Available from: www.bbc.com/news/world-asia-32492232
  • [5] Y.H. Lin, R. Batta, P.A. Rogerson, A. Blatt, M. Flanigan, A logistics model for emergency supply of critical items in the aftermath of a disaster, Socio-Economic Planning Sciences 45/4 (2011) 132-145. DOI: https://doi.org/10.1016/j.seps.2011.04.003
  • [6] S.K. Jain, S. Pathak, Intensity Based Casualty Models: Case Study of Bhuj and Latur Earthquake in India, Proceedings of the 15th World Conference on Earthquake Engineering, 2012, Lisbon, Portugal, 1-10.
  • [7] A. Jeffery, Global disasters in 2017 caused an estimated $306 billion in economic losses, says Swiss Re, Available from: https://www.cnbc.com/2017/12/20/swiss-re-global-disasters-push-2017-economic-losses-to-306-billion.html
  • [8] D. Sarma, A. Das, U.K. Bera, An optimal redistribution plan considering aftermath disruption in disaster management, Soft Computing 24/1 (2020) 65-82. DOI: https://doi.org/10.1007/s00500-019-04287-7
  • [9] M.O. Soto, L.T. Marquez, Best and Worst Resilience Practices Adopted by the Food and beverages Supply Chain in the Aftermath of Natural disaster, Resiliency and Business Innovation Program, 2020. Available from: https://researchresourcelibrary.com/wp-content/uploads/2021/01/BESTWORST_PDF.pdf
  • [10] Z. Ghaffari, M.M. Nasiri, A. Bozorgi-Amiri, A. Rahbari, Emergency supply chain scheduling problem with multiple resources in disaster relief operations. Transportmetrica A: Transport Science 16/3 (2020) 930-956. DOI: https://doi.org/10.1080/23249935.2020.1720858
  • [11] N. Ng, Nepal Struggles to Cope with International Aid. Available from: https://edition.cnn.com/2015/04/28/asia/nepal-earthquake-aid-struggle/index.html
  • [12] UNISDR Terminology on Disaster Risk Reduction, UNISDR, Geneva, Switzerland, 2009. Available from: https://www.unisdr.org/files/7817_UNISDRTerminologyEnglish.pdf
  • [13] National Disaster Management Plan, National Disaster Management Authority Government of India, New Delhi, 2016. Available from: https://www.mha.gov.in/sites/default/files/National%20Disaster%20Management%20Plan%20May%202016.pdf
  • [14] 2015 Nepal Earthquake Anniversary. Available from: https://www.usaid.gov/nepal-earthquake
  • [15] Press Information Bureau, Government of India, Ministry of Defence, Army Launches Operation Maitri. Available from: http://pib.nic.in/newsite/PrintRelease.aspx?relid=118739
  • [16] M. Eftekhar, J.-S.J. Song, S. Webster, Prepositioning and Local Purchasing for Emergency Operations Under Budget, Demand, and Supply Uncertainty, Manufacturing and Service Operations Management (2021) (Available online). DOI: https://doi.org/10.1287/msom.2020.0956
  • [17] A. Kumar, Traffic Characteristics and Junction Improvement. Relationship Between Traffic Conflicts and Accidents, Lap Lambert Academic Publishing, Republic of Moldovia, 2021.
  • [18] A. Kumar, Traffic Studies for Junction Improvement of Major Roads in Jalandhar City, Proceedings of the National Conference on Engineering Research and Applications “ERA’2016”, Chandigarh, 2016, 245-248.
  • [19] G.B. Dantzig, Linear programming under uncertainty, Management Science 1/3-4 (1955) 197-206.
  • [20] J.R. Birge, F. Louveaux, Introduction to Stochastic Programming, Springer, New York, 1997. DOI: https://doi.org/10.1007/978-1-4614-0237-4
  • [21] P. Kall, S.W. Wallace, Stochastic Programming, John Wiley and Sons, Chichester, 1994.
  • [22] J.M. Mulvey, R.J. Vanderbei, S.A. Zenios, Robust optimization of large-scale systems, Operations Research 43/2 (1995) 264-281. DOI: https://doi.org/10.1287/opre.43.2.264
  • [23] A. Shapiro, T. Homem-de Mello, A simulation-based approach to the two-stage stochastic programming with recourse, Mathematical Programming 81 (1998) 301-325. DOI: https://doi.org/10.1007/BF01580086
  • [24] S.W. Wallace, Solving stochastic programs with network recourse, Networks 16/3 (1986) 295-317. DOI: https://doi.org/10.1002/net.3230160306
  • [25] G.D. Glockner, G.L. Nemhauser, A dynamic network flow problem with uncertain arc capacities: formulation and problem structure, Operations Research 48/2 (2000) 233-242. DOI: https://doi.org/10.1287/opre.48.2.233.12384
  • [26] G. Barbarosoglu, L. Ozdamar, A. Cevik, An interactive approach for hierarchical analysis of helicopter logistics in disaster relief operations, European Journal of Operational Research 140/1 (2002) 118-133. DOI: https://doi.org/10.1016/S0377-2217(01)00222-3
  • [27] K.M. Bryson, H. Miller, A. Joseph, A. Mobolurin, Using formal MS/OR modeling to support disaster recovery planning, European Journal of Operational Research 141/3 (2002) 679-688. DOI: https://doi.org/10.1016/S0377-2217(01)00275-2
  • [28] G. Galindo, R. Batta, Review of recent development in OR research in disaster operations management. European Journal of Operational Research 230/2 (2013) 201-211. DOI: https://doi.org/10.1016/j.ejor.2013.01.039
  • [29] M.C. Hoyos, R.S. Morales, R. Akhavan-Tabatabei, OR models with stochastic components in disaster operations management: A literature survey, Computer and Industrial Engineering 82 (2015) 183-197. DOI: https://doi.org/10.1016/j.cie.2014.11.025
  • [30] C.-C. Lu, K.-C. Ying, H.-J. Chen, Real-time relief distribution in the aftermath of disasters - A rolling horizon approach, Transportation Research Part E: Logistics and Transportation Review 93 (2016) 1-20. DOI: https://doi.org/10.1016/j.tre.2016.05.002
  • [31] National Disaster Management Authority, Disaster Management Cycle, Available from: http://www.ndma.gov.in/images/vulnerability/DM20Cycle.jpg
  • [32] A. Poddar, A. Kumar, Public Transportation System Reliability and Safety. Challenges and Opportunities in Public Transportation, Lap Lambert Academic Publishing, Republic of Moldovia, 2021.
Uwagi
PL
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
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