PDF
Abstract
Cross-regional allocation is necessary for the rational utilization and optimal allocation of resources. It is also the key to effective and sustainable disaster relief. Existing research, however, generally centers on emergency resource allocation only within territories or regions. This article proposes a multiperiod allocation optimization model for emergency resources based on regional self-rescue and cross-regional collaborative rescue efforts. The model targets the shortest delivery time and lowest allocation costs as its efficiency goals and the maximum coverage rate of resource allocation in the disaster-affected locations as its equity goal. An objective weighting fuzzy algorithm based on two-dimensional Euclidean distance is designed to solve the proposed model. A case study based on the Wenchuan Earthquake of 12 May 2008 was conducted to validate the proposed model. The results indicate that our proposed model allows for optimal, multiperiod cross-regional resource allocation by combining interterritorial and nearby allocation principles. Cross-regional relief makes resource allocation more equitable, minimizes dissatisfaction, and prevents losses. Different decision preferences appear to significantly affect the choice of resource allocation scheme employed, which provides flexibility for decision making in different emergencies.
Keywords
Cross-regional collaborative rescue
/
Efficiency and equity
/
Emergency resource allocation
/
Multiperiod allocation
/
Wenchuan Earthquake
Cite this article
Download citation ▾
Yanyan Wang.
Multiperiod Optimal Allocation of Emergency Resources in Support of Cross-Regional Disaster Sustainable Rescue.
International Journal of Disaster Risk Science, 2021, 12(3): 394-409 DOI:10.1007/s13753-021-00347-5
| [1] |
Amailef K, Lu J. Ontology-supported case-based reasoning approach for intelligent m-Government emergency response services. Decision Support Systems, 2013, 55(1): 79-97.
|
| [2] |
Ansell C, Boin A, Keller A. Managing transboundary crises: Identifying the building blocks of an effective response system. Journal of Contingencies and Crisis Management, 2010, 18(4): 195-207.
|
| [3] |
Arora H, Raghu TS, Vinze A. Resource allocation for demand surge mitigation during disaster response. Decision Support Systems, 2010, 50(1): 304-315.
|
| [4] |
Arrubla JAG, Ntaimo L, Stripling C. Wildfire initial response planning using probabilistically constrained stochastic integer programming. International Journal of Wildland Fire, 2014, 23(6): 825-838.
|
| [5] |
Balcik B, Beamon BM. Facility location in humanitarian relief. International Journal of Logistics Research and Applications, 2008, 11(2): 101-121.
|
| [6] |
Barbarosoğlu G, Özdamar L, Çevik A. An interactive approach for hierarchical analysis of helicopter logistics in disaster relief operations. European Journal of Operational Research, 2002, 140(1): 118-133.
|
| [7] |
Berkoune D, Renaud J, Rekik M, Ruiz A. Transportation in disaster response operations. Socio-Economic Planning Sciences, 2012, 46(1): 23-32.
|
| [8] |
Bertsimas D, Farias VF, Trichakis N. On the efficiency-fairness trade-off. Management Science, 2012, 58(12): 2234-2250.
|
| [9] |
Boin A, Rhinard M, Ekengren M. Managing transboundary crises: The emergence of European union capacity. Journal of Contingencies and Crisis Management, 2014, 22(3): 131-142.
|
| [10] |
Calixto E, Larouvere EL. The regional emergency plan requirement: Application of the best practices to the Brazilian case. Safety Science, 2010, 48(8): 991-999.
|
| [11] |
Cao CJ, Li CD, Qu T, Yang Q. A bi-level programming model for relief trans-regional scheduling: Taking into consideration survivors’ perceived satisfaction and risk acceptability. Journal of Management Sciences in China, 2019, 22(9): 111-126 in Chinese
|
| [12] |
Cao J, Zhu L. Super-network model of urban agglomeration emergency coordination considering decision preferences. Journal of Management Sciences in China, 2014, 17(11): 33-42 in Chinese
|
| [13] |
Chang MS, Tseng YL, Chen JW. A scenario planning approach for the flood emergency logistics preparation problem under uncertainty. Transportation Research Part E: Logistics and Transportation Review, 2007, 43(6): 737-754.
|
| [14] |
China Earthquake Administration. 2012. Earthquake Emergency Rescue Plan. http://www.cea.gov.cn/publish/dizhenj/119/100136/20121130104213119243137/index.html. Accessed 16 May 2020 (in Chinese).
|
| [15] |
China News Network. 2008. Sichuan Wenchuan earthquake has confirmed 69,227 people killed, 17,923 missing. http://www.chinanews.com/gn/news/2008/09-25/1394600.shtml. Accessed 16 May 2020 (in Chinese).
|
| [16] |
Cotes N, Cantillo V. Including deprivation costs in facility location models for humanitarian relief logistics. Socio-Economic Planning Sciences, 2019, 65: 89-100.
|
| [17] |
Equi L, Gallo G, Marziale S, Weintraub A. A combined transportation and scheduling problem. European Journal of Operational Research, 1997, 97(1): 94-104.
|
| [18] |
Eshghi K, Larson RC. Disasters: Lessons from the past 105 years. Disaster Prevention and Management, 2008, 17(1): 62-82.
|
| [19] |
Green LV, Kolesar PJ. Improving emergency responsiveness with management science. Management Science, 2004, 50(8): 1001-1014.
|
| [20] |
Green HK, Lysaght O, Saulnier DD, Blanchard K, Humphrey A, Fakhruddin B, Murray V. Challenges with disaster mortality data and measuring progress towards the implementation of the Sendai framework. International Journal of Disaster Risk Science, 2019, 10(4): 449-461.
|
| [21] |
Groothedde B, Ruijgrok C, Tavasszy L. Towards collaborative, intermodal hub networks: A case study in the fast moving consumer goods market. Transportation Research Part E: Logistics and Transportation Review, 2015, 41(6): 567-583.
|
| [22] |
Guo, Y., Y. Ye, Q. Yang, and K. Yang. 2019. A multi-objective INLP model of sustainable resource allocation for long-range Maritime search and rescue. Sustainability 11(3): Article 929.
|
| [23] |
Haghani A, Oh S-C. Formulation and solution of a multi-commodity, multi-modal network flow model for disaster relief operations. Transportation Research Part A: Policy and Practice, 1996, 30(3): 231-250.
|
| [24] |
Holguín-Veras J, Pérez N, Jaller M, Van Wassenhove LN, Aros-Vera F. On the appropriate objective function for post-disaster humanitarian logistics models. Journal of Operations Management, 2013, 31(5): 262-280.
|
| [25] |
Hoyos MC, Morales RS, Akhavan-Tabatabaei R. OR models with stochastic components in disaster operations management: A literature survey. Computers & Industrial Engineering, 2015, 82: 183-197.
|
| [26] |
Hu CL, Liu X, Hua YK. A bi-objective robust model for emergency resource allocation under uncertainty. International Journal of Production Research, 2016, 54(24): 7421-7438.
|
| [27] |
Hu XB, Wang M, Ye T, Shi P. A new method for resource allocation optimization in disaster reduction and risk governance. International Journal of Disaster Risk Science, 2016, 7(2): 138-150.
|
| [28] |
Huang K, Rafiei R. Equitable last mile distribution in emergency response. Computers & Industrial Engineering, 2019, 127(1): 887-900.
|
| [29] |
Kutanoglu E, Mahajan M. An inventory sharing and allocation method for a multi-location service parts logistics network with time-based service levels. European Journal of Operational Research, 2009, 194(3): 728-742.
|
| [30] |
Li, A.N., X.Q. Deng, and Q.H. Zhao. 2017. Unconventional emergency coordinated organization based on fractal perspective. Systems Engineering—Theory & Practice 37(4): 937–948 (in Chinese).
|
| [31] |
Li J, Li QR, Liu C, Ullah Khan S, Ghani N. Community-based collaborative information system for emergency management. Computers & Operations Research, 2014, 42: 116-124.
|
| [32] |
Liu Y, Cui N, Zhang JH. Integrated temporary facility location and casualty allocation planning for post-disaster humanitarian medical service. Transportation Research Part E: Logistics and Transportation Review, 2019, 128: 1-16.
|
| [33] |
Liu DH, Zhao N, Zou HW. Multi-period reputation effect model of governmental emergency strategy in environmental pollution incidents. Management Review, 2018, 30(9): 239-245 in Chinese
|
| [34] |
Luss H. On equitable resource allocation problems: A lexicographic minimax approach. Operations Research, 1999, 47(3): 361-378.
|
| [35] |
Lv T, Nie Y, Wang CL, Gao J. Cross-regional emergency scheduling planning for petroleum based on the supernetwork model. Petroleum Science, 2018, 15: 666-679.
|
| [36] |
Minas J, Hearne J, Martell D. An integrated optimization model for fuel management and fire suppression preparedness planning. Annals of Operations Research, 2015, 232(1): 201-215.
|
| [37] |
Najafi M, Eshghi K, Dullaert W. A multi-objective robust optimization model for logistics planning in the earthquake response phase. Transportation Research Part E: Logistics and Transportation Review, 2013, 49(1): 217-249.
|
| [38] |
Ogie RI, Pradhan B. Natural hazards and social vulnerability of place: The strength-based approach applied to Wollongong, Australia. International Journal of Disaster Risk Science, 2019, 10(3): 404-420.
|
| [39] |
Olsson EK. Transboundary crisis networks: The challenge of coordination in the face of global threats. Risk Management, 2015, 17(2): 91-108.
|
| [40] |
Özdamar L, Ertem MA. Models, solutions and enabling technologies in humanitarian logistics. European Journal of Operational Research, 2015, 244(1): 55-65.
|
| [41] |
Özdamar L, Ekinci E, Küçükyazici B. Emergency logistics planning in natural disasters. Annals of Operations Research, 2004, 129(1–4): 217-245.
|
| [42] |
Qin, J., Y. Ye, B. Cheng, X. Zhao, and L. Ni. 2017. The emergency vehicle routing problem with uncertain demand under sustainability environments. Sustainability 9(2): Article 288.
|
| [43] |
Qiu Y, Shi XL, Hua GW. Regional cooperative strategies for emergency response to accidents and disasters under longitudinal administrative constraint—Case study in Beijing-Tianjin-Hebei region. Management Review, 2019, 31(8): 240-249 in Chinese
|
| [44] |
Rose A, Kustra T. Economic considerations in designing emergency management institutions and policies for transboundary disasters. Public Management Review, 2013, 15(3): 446-462.
|
| [45] |
Shao M, Song Y, Teng C, Zhang Z. Algorithms and simulation of multi-level and multi-coverage on cross-reginal emergency facilities. Wireless Personal Communications: An International Journal, 2018, 102(4): 3663-3676.
|
| [46] |
Sheu J-B, Pan C. A method for designing centralized emergency supply network to respond to large-scale natural disasters. Transportation Research Part B: Methodological, 2014, 67: 284-305.
|
| [47] |
Tang WQ, Tang WM, Zhang M. Scheduling of emergency commodities: Theory and method, 2012, Beijing: Science Press in Chinese
|
| [48] |
Toro-Díaz H, Mayorga ME, Chanta S, McLay LA. Joint location and dispatching decisions for emergency medical services. Computers & Industrial Engineering, 2013, 64(4): 917-928.
|
| [49] |
Tüfeki S. An integrated emergency management decision support system for hurricane emergencies. Safety Science, 1995, 20(1): 39-48.
|
| [50] |
Tzeng GH, Cheng HJ, Huang TD. Mufti-objective optimal planning for designing relief delivery systems. Transportation Research Part E: Logistics and Transportation Review, 2007, 43(6): 673-686.
|
| [51] |
Wang X, Lv S. Research on across-regional public emergencies cooperation system based on knowledge collaboration. Science and Technology Management Research, 2016, 8: 216-221 in Chinese
|
| [52] |
Wang Y, Sun B. A multiobjective allocation model for emergency resources that balance efficiency and fairness. Mathematical Problems in Engineering, 2018
|
| [53] |
Wang Y, Sun B. Multi-period optimization model of multi-type emergency materials allocation based on fuzzy information. Chinese Journal of Management Science, 2020, 28(3): 40-51 in Chinese
|
| [54] |
Wang Y, Bier VM, Sun B. Measuring and achieving equity in multiperiod emergency material allocation. Risk Analysis, 2019, 39(11): 2408-2426.
|
| [55] |
Wex F, Schryen G, Feuerriegel S, Neumann D. Emergency response in natural disaster management: Allocation and scheduling of rescue units. European Journal of Operational Research, 2014, 235(3): 697-708.
|
| [56] |
Xu J, Li J. Theory and method of multi-objective decision making, 2005, Beijing: Tsinghua University Press in Chinese
|
| [57] |
Xu SH, Han CF, Meng LP, Wu QD. Research on the adoption of an emergency management organization system based on the NK model. Systems Engineering—Theory & Practice, 2017, 37(6): 1619-1629 in Chinese
|
| [58] |
Yao C, Xiao X. Method for the problem of multi-objective decision making based on fuzzy math theory. Journal of Wuhan University Technology Transportation Science & Engineering, 2006, 30(4): 700-703 in Chinese
|
| [59] |
Yi W, Özdamar L. A dynamic logistics coordination model for evacuation and support in disaster response activities. European Journal of Operational Research, 2007, 179(3): 1177-1193.
|
| [60] |
Zhan SL, Liu N, Ye Y. Coordinating efficiency and equity in disaster relief logistics via information updates. International Journal of Systems Science, 2014, 45(8): 1607-1621.
|
| [61] |
Zhang F, Gao Y, Li YL. Research on cross-regional emergency scheduling and allocating strategies. International Journal of Grid and Distributed Computing, 2016, 9(5): 89-98.
|
| [62] |
Zhao M, Liu X. Reprint of: Regional risk assessment for urban major hazards based on GIS geoprocessing to improve public safety. Safety Science, 2017, 97: 112-119.
|
| [63] |
Zhou S, Erdogan A. A spatial optimization model for resource allocation for wildfire suppression and resident evacuation. Computers & Industrial Engineering, 2019, 138(1): 1-16.
|
| [64] |
Zhou Y, Liu J, Zhang Y, Gan X. A multi-objective evolutionary algorithm for multi-period dynamic emergency resource scheduling problems. Transportation Research Part E: Logistics and Transportation Review, 2017, 99: 77-95.
|
| [65] |
Zhu L, Guo D, Gu J, Du YQ. System dynamics analysis of cross-regional coordinative emergency materials allocation under severe epidemics—A case study on H1N1 joint response in the Yangtze River Delta. Systems Engineering, 2017, 35(6): 105-112 in Chinese
|