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Stochastic optimization for investment in facilities in emergency prevention

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  • Hu, Shao-Long
  • Han, Chuan-Feng
  • Meng, Ling-Peng

Abstract

A coordinated approach is developed to integrate three preventive measures (i.e. building reinforcement, reinforcement of road networks, and facility location of relief supplies), with the objectives of minimizing budgets and risk-induced penalties. The Conditional Value-at-Risk is employed as a decision-making tool to evaluate diverse decisions of prevention based on the degree of risk aversion. Based on a real-world case of an earthquake, a series of scenarios were designed, and the applicability of the proposed model was studied. The coordinated approach for investing preventive measures is cost-efficient in helping reduce the impact of disaster on society.

Suggested Citation

  • Hu, Shao-Long & Han, Chuan-Feng & Meng, Ling-Peng, 2016. "Stochastic optimization for investment in facilities in emergency prevention," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 89(C), pages 14-31.
  • Handle: RePEc:eee:transe:v:89:y:2016:i:c:p:14-31
    DOI: 10.1016/j.tre.2016.02.006
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    1. Mete, Huseyin Onur & Zabinsky, Zelda B., 2010. "Stochastic optimization of medical supply location and distribution in disaster management," International Journal of Production Economics, Elsevier, vol. 126(1), pages 76-84, July.
    2. Eskandarzadeh, Saman & Eshghi, Kourosh, 2013. "Decision tree analysis for a risk averse decision maker: CVaR Criterion," European Journal of Operational Research, Elsevier, vol. 231(1), pages 131-140.
    3. de la Torre, Luis E. & Dolinskaya, Irina S. & Smilowitz, Karen R., 2012. "Disaster relief routing: Integrating research and practice," Socio-Economic Planning Sciences, Elsevier, vol. 46(1), pages 88-97.
    4. Jotshi, Arun & Gong, Qiang & Batta, Rajan, 2009. "Dispatching and routing of emergency vehicles in disaster mitigation using data fusion," Socio-Economic Planning Sciences, Elsevier, vol. 43(1), pages 1-24, March.
    5. Keefer, Philip & Neumayer, Eric & Plümper, Thomas, 2011. "Earthquake Propensity and the Politics of Mortality Prevention," World Development, Elsevier, vol. 39(9), pages 1530-1541, September.
    6. Rawls, Carmen G. & Turnquist, Mark A., 2010. "Pre-positioning of emergency supplies for disaster response," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 521-534, May.
    7. Ahmadi-Javid, Amir & Seddighi, Amir Hossein, 2013. "A location-routing problem with disruption risk," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 53(C), pages 63-82.
    8. Hu, Zhi-Hua & Sheu, Jiuh-Biing & Xiao, Ling, 2014. "Post-disaster evacuation and temporary resettlement considering panic and panic spread," Transportation Research Part B: Methodological, Elsevier, vol. 69(C), pages 112-132.
    9. Edrissi, Ali & Nourinejad, Mehdi & Roorda, Matthew J., 2015. "Transportation network reliability in emergency response," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 80(C), pages 56-73.
    10. Sawik, Tadeusz, 2014. "Joint supplier selection and scheduling of customer orders under disruption risks: Single vs. dual sourcing," Omega, Elsevier, vol. 43(C), pages 83-95.
    11. Ahmadi, Morteza & Seifi, Abbas & Tootooni, Behnam, 2015. "A humanitarian logistics model for disaster relief operation considering network failure and standard relief time: A case study on San Francisco district," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 75(C), pages 145-163.
    12. Rennemo, Sigrid Johansen & Rø, Kristina Fougner & Hvattum, Lars Magnus & Tirado, Gregorio, 2014. "A three-stage stochastic facility routing model for disaster response planning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 62(C), pages 116-135.
    13. Lili Du & Srinivas Peeta, 2014. "A Stochastic Optimization Model to Reduce Expected Post-Disaster Response Time Through Pre-Disaster Investment Decisions," Networks and Spatial Economics, Springer, vol. 14(2), pages 271-295, June.
    14. Galindo, Gina & Batta, Rajan, 2013. "Review of recent developments in OR/MS research in disaster operations management," European Journal of Operational Research, Elsevier, vol. 230(2), pages 201-211.
    15. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
    16. Wang, Haijun & Du, Lijing & Ma, Shihua, 2014. "Multi-objective open location-routing model with split delivery for optimized relief distribution in post-earthquake," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 69(C), pages 160-179.
    17. Kelle, Peter & Schneider, Helmut & Yi, Huizhi, 2014. "Decision alternatives between expected cost minimization and worst case scenario in emergency supply – Second revision," International Journal of Production Economics, Elsevier, vol. 157(C), pages 250-260.
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    1. Zhang, Guowei & Jia, Ning & Zhu, Ning & He, Long & Adulyasak, Yossiri, 2023. "Humanitarian transportation network design via two-stage distributionally robust optimization," Transportation Research Part B: Methodological, Elsevier, vol. 176(C).
    2. Zhizhu Lai & Qun Yue & Zheng Wang & Dongmei Ge & Yulong Chen & Zhihong Zhou, 2022. "The min-p robust optimization approach for facility location problem under uncertainty," Journal of Combinatorial Optimization, Springer, vol. 44(2), pages 1134-1160, September.
    3. Dönmez, Zehranaz & Kara, Bahar Y. & Karsu, Özlem & Saldanha-da-Gama, Francisco, 2021. "Humanitarian facility location under uncertainty: Critical review and future prospects," Omega, Elsevier, vol. 102(C).
    4. Hu, Shaolong & Hu, Qingmi & Tao, Sha & Dong, Zhijie Sasha, 2023. "A multi-stage stochastic programming approach for pre-positioning of relief supplies considering returns," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).
    5. Ju He & Yunxiao Dang & Wenzhong Zhang & Li Chen, 2020. "Perception of Urban Public Safety of Floating Population with Higher Education Background: Evidence from Urban China," IJERPH, MDPI, vol. 17(22), pages 1-16, November.
    6. Yücel, E. & Salman, F.S. & Arsik, I., 2018. "Improving post-disaster road network accessibility by strengthening links against failures," European Journal of Operational Research, Elsevier, vol. 269(2), pages 406-422.
    7. Zhong, Shaopeng & Cheng, Rong & Jiang, Yu & Wang, Zhong & Larsen, Allan & Nielsen, Otto Anker, 2020. "Risk-averse optimization of disaster relief facility location and vehicle routing under stochastic demand," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).

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