A Comparative Analysis on Dispatching of Post-Disaster Search and Rescue

Qianqian Liu

Abstract


The development of electronic information technology provides technique and equipment support for post-disaster search and rescue (SAR). It has also changed the operation pattern of SAR. Two basic types of SAR pattern are proposed here: central dispatch and independent search. The former pattern depends on a unified SAR management system, while the latter carries out independently according to instantaneous information. The research studies the corresponding conditions of SAR, models and algorithms. The idea of central dispatch is raised through dispatching rules, transforming independent search into a problem of network flow equilibrium. The validity of the model is verified by numerical examples. The results show that the central dispatch helps to distribute rescue forces to the most needed area, and the independent search based on real-time information indicates better effect, considering that the independent search takes both distributions of survivors and SAR teams into consideration. The results revealed in the numerical examples support the conclusion.


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Ambrosino D., Scutella M.G. (2005). Distribution network design: new problems and related models, European Journal of Operational Research, 165(3), 610-624.

Cho S., Gordon P., Moore J., Richardson H.W., Shinozuka M., Chang S. (2001). Integrating transportation network and grgional economic models to estimate the costs of a large urban earthquake, Journal of Regional Science, 41(1), 39-65

Danielsson M., Ohlsson K. (1999). Decision Making in Emergency Management: A Survey Study, International Journal of Cognitive Ergonomics, 3(2), 91-99.

Fiedrich F., Gehbauer F., Rickers U. (2000). Optimized resource allocation for emergency response after earthquake disasters, Safety Science, 35(1-3), 41-57.

Glickman T.S., Erkut E. J. (2007). Assessment of hazardous material risks for rail yard safety, Safety Science, 45, 813-822.

Haghani A., Oh S.C. (1996). Formulation and solution of a multi-commodity multi-modal network flow model for disaster relief operations, Transportation Research Part A, 30(3), 231-250.

Hu C., Li K.P. (2011). Research of earthquake relief simulation based on Levy Flight (Chinese), Science Technology and Engineering, 11(25), 6126-6131.

Janis I.L., Mann L. (1977). Emergency decision making: a theoretical analysis of responses to disaster warnings, Journal of Human Stress, 3, 35-45.

Jotshi A., Batta R., Gong Q. (2009). Dispatching and routing of emergency vehicles in disaster mitigation using data fusion. Socio-Economic Planning Sciences, 43(1), 1-24.

Kapucu N., Garayev V. (2011). Collaborative Decision-Making in Emergency and Disaster Management, International Journal of Public Administration, 34(6), 366–375. DOI: 10.1080/01900692.2011.561477

Lin P., Lo S.M., Huang H.C., Yuen K.K. (2008). On the use of multi-stage time-varying quickest time approach for optimization of evacuation planning. Fire Safety Journal, 43(4), 282-290.

Liu Q., Wang Q. (2016), A Team Distribution Model of Post-Disaster Search and Rescue Considering Information Accuracy Difference, Chemical Engineering Transactions, 51, 877-882.

Meng Q., Yang H. (2002). Benefit distribution and equity in road network design, Transportation Research Part B: Methodological, 36(1), 19-35.

Mirjazaee N., Moghim, N. (2015). An opportunistic routing based on symmetrical traffic distribution in vehicular networks, Computers and Electrical Engineering, 47, 1-12.

Mirandola A., Lorenzini E. (2016). Energy, Environment and Climate: from the past to the future, International Journal of Heat and Technology, 34(2), 159-164.

Saadatseresht M., Mansourian A., Taleai M. (2009). Evacuation planning using multiobjective evolutionary optimization approach, European Journal of Operational Research, 198(1), 305-314.

Stepanov A., Smith J-M.G. (2009). Multi-objective evacuation routing in transportation networks, European Journal of Operational Research, 198(2), 435-446.

Sheu J-B. (2007). Challenges of Emergency Logistics Management. Transportation Research Part E: Logistics and Transportation Review, 43(6), 655-659.

Shi M., Chen J.P., Sun D.Y., Cao C. (2015), Hazard assement of debris flows based on the catastrophe progression method: a case study from the Wudongde Dam Site, International Journal of Heat and Technology, 33(4), 217-220.

Takeo Y. (1996). A network flow approach to a city emergency evacuation planning, International Journal of System Science, 27(10), 931-936.

Waugh W.L., Streib G. (2006). Collaboration and leadership for effective emergency management, Public Administration Review, 66(s1), 131-140.

Yuan Y., Wang D.W.(2009). Path selection model and algorithm for emergency logistics management, Computers & industrial engineering, 56(3), 1081-1094.

Zhang X.G., Zhang Z.L., Zhang Y.J., Wei D.J., Deng Y. (2013). Route selection for emergency logistics management: a bio-inspired algorithm, Safety Science, 54, 87-91.


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