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A Voting TOPSIS Approach for Determining the Priorities of Areas Damaged in Disasters

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  • Yanjin He

    (Graduate School of Logistics, Inha University, Incheon 22212, Korea)

  • Hosang Jung

    (Asia Pacific School of Logistics, Inha University, Incheon 22212, Korea)

Abstract

In this paper, we investigate the priority determination problem for areas that have been damaged during disasters. Relief distribution should be planned while considering the priorities of the damaged areas. To determine the priorities of the damaged areas, we first define four criteria and then propose a voting TOPSIS (technique for order of preference by similarity to ideal solution) that utilizes the fuzzy pair-wise comparison, data envelopment analysis, and TOPSIS. Since the voting TOPSIS is based on the voting results of multiple experts, it can be applied to urgent situations quickly, regardless of the consistency of comparison, the number of alternatives, and the number of participating experts. The proposed approach is validated using a real-world case, and this case analysis shows that the voting TOPSIS is viable.

Suggested Citation

  • Yanjin He & Hosang Jung, 2018. "A Voting TOPSIS Approach for Determining the Priorities of Areas Damaged in Disasters," Sustainability, MDPI, vol. 10(5), pages 1-16, May.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:5:p:1607-:d:146848
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    References listed on IDEAS

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    1. Kuo, Ting, 2017. "A modified TOPSIS with a different ranking index," European Journal of Operational Research, Elsevier, vol. 260(1), pages 152-160.
    2. Sheu, Jiuh-Biing, 2007. "An emergency logistics distribution approach for quick response to urgent relief demand in disasters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(6), pages 687-709, November.
    3. Yi, Wei & Ozdamar, Linet, 2007. "A dynamic logistics coordination model for evacuation and support in disaster response activities," European Journal of Operational Research, Elsevier, vol. 179(3), pages 1177-1193, June.
    4. Afshar, Abbas & Haghani, Ali, 2012. "Modeling integrated supply chain logistics in real-time large-scale disaster relief operations," Socio-Economic Planning Sciences, Elsevier, vol. 46(4), pages 327-338.
    5. Hosang Jung, 2017. "Evaluation of Third Party Logistics Providers Considering Social Sustainability," Sustainability, MDPI, vol. 9(5), pages 1-18, May.
    6. Rivera-Royero, Daniel & Galindo, Gina & Yie-Pinedo, Ruben, 2016. "A dynamic model for disaster response considering prioritized demand points," Socio-Economic Planning Sciences, Elsevier, vol. 55(C), pages 59-75.
    7. Sheu, Jiuh-Biing, 2010. "Dynamic relief-demand management for emergency logistics operations under large-scale disasters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(1), pages 1-17, January.
    8. Opricovic, Serafim & Tzeng, Gwo-Hshiung, 2004. "Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS," European Journal of Operational Research, Elsevier, vol. 156(2), pages 445-455, July.
    9. Caunhye, Aakil M. & Nie, Xiaofeng & Pokharel, Shaligram, 2012. "Optimization models in emergency logistics: A literature review," Socio-Economic Planning Sciences, Elsevier, vol. 46(1), pages 4-13.
    10. Liu, Fuh-Hwa Franklin & Hai, Hui Lin, 2005. "The voting analytic hierarchy process method for selecting supplier," International Journal of Production Economics, Elsevier, vol. 97(3), pages 308-317, September.
    11. Özdamar, Linet & Ertem, Mustafa Alp, 2015. "Models, solutions and enabling technologies in humanitarian logistics," European Journal of Operational Research, Elsevier, vol. 244(1), pages 55-65.
    12. Noham, Reut & Tzur, Michal, 2018. "Designing humanitarian supply chains by incorporating actual post-disaster decisions," European Journal of Operational Research, Elsevier, vol. 265(3), pages 1064-1077.
    13. Nilay Noyan & Burcu Balcik & Semih Atakan, 2016. "A Stochastic Optimization Model for Designing Last Mile Relief Networks," Transportation Science, INFORMS, vol. 50(3), pages 1092-1113, August.
    14. Erica Gralla & Jarrod Goentzel & Charles Fine, 2014. "Assessing Trade-offs among Multiple Objectives for Humanitarian Aid Delivery Using Expert Preferences," Production and Operations Management, Production and Operations Management Society, vol. 23(6), pages 978-989, June.
    15. Gutjahr, Walter J. & Nolz, Pamela C., 2016. "Multicriteria optimization in humanitarian aid," European Journal of Operational Research, Elsevier, vol. 252(2), pages 351-366.
    16. Y M Wang & K S Chin & J B Yang, 2007. "Three new models for preference voting and aggregation," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(10), pages 1389-1393, October.
    17. Lin, Yen-Hung & Batta, Rajan & Rogerson, Peter A. & Blatt, Alan & Flanigan, Marie, 2011. "A logistics model for emergency supply of critical items in the aftermath of a disaster," Socio-Economic Planning Sciences, Elsevier, vol. 45(4), pages 132-145, December.
    18. Sawada, Yasuyuki & Takasaki, Yoshito, 2017. "Natural Disaster, Poverty, and Development: An Introduction," World Development, Elsevier, vol. 94(C), pages 2-15.
    19. Wade D. Cook & Moshe Kress, 1990. "A Data Envelopment Model for Aggregating Preference Rankings," Management Science, INFORMS, vol. 36(11), pages 1302-1310, November.
    20. Jiazhen Peng & Xiaojun Shan & Yang Gao & Yohannes Kesete & Rachel Davidson & Linda Nozick & Jamie Kruse, 2014. "Modeling the integrated roles of insurance and retrofit in managing natural disaster risk: a multi-stakeholder perspective," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 74(2), pages 1043-1068, November.
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