Citation: | Xia Li, Yuewen Xiao, Jiaxuan Li, Haipeng Wang, Eryong Chuo, Haili Bai. Special Emergency Resources Preallocation Concerning Demand Time for Tunnel Collapse[J]. International Journal of Disaster Risk Science, 2023, 14(1): 113-126. doi: 10.1007/s13753-023-00470-5 |
Akgün, İ, F. Gümüşbuğa, and B. Tansel. 2015. Risk based facility location by using fault tree analysis in disaster management. Omega 52: 168–179.
|
Atta, S., P.R. Sinha Mahapatra, and A. Mukhopadhyay. 2019. Multi-objective uncapacitated facility location problem with customers’ preferences: Pareto-based and weighted sum GA-based approaches. Soft Computing 23(23): 12347–12362.
|
Berman, O., Z. Drezner, and D. Krass. 2010. Generalized coverage: New developments in covering location models. Computers and Operations Research 37(10): 1675–1687.
|
Boonmee, C., M. Arimura, and T. Asada. 2017. Facility location optimization model for emergency humanitarian logistics. International Journal of Disaster Risk Reduction 24: 485–498.
|
Bozorgi-Amiri, A., and M. Khorsi. 2016. A dynamic multi-objective location–routing model for relief logistic planning under uncertainty on demand, travel time, and cost parameters. The International Journal of Advanced Manufacturing Technology 85(5–8): 1633–1648.
|
Chanta, S., M.E. Mayorga, and L.A. McLay. 2014. Improving emergency service in rural areas: A bi-objective covering location model for EMS systems. Annals of Operations Research 221(1): 133–159.
|
Church, R., and C. ReVelle. 1974. The maximal covering location problem. Papers of the Regional Science Association 32(1): 101–118.
|
Coutinho-Rodrigues, J., L. Tralhão, and L. Alçada-Almeida. 2012. Solving a location-routing problem with a multi-objective approach: The design of urban evacuation plans. Journal of Transport Geography 22: 206–218.
|
David, S., and B. Luc. 2022. Does every minute really count? Road time as an indicator for the economic value of emergency medical services. Value in Health 25(3): 400–408.
|
Díaz, J.A., D.E. Luna, J.F. Camacho-Vallejo, and M.S. Casas-Ramírez. 2017. GRASP and hybrid GRASP-Tabu heuristics to solve a maximal covering location problem with customer preference ordering. Expert Systems with Applications 82: 67–76.
|
Falcón-Cardona, J.G., and C.A.C. Coello. 2020. Indicator-based multi-objective evolutionary algorithms. ACM Computing Surveys 53(2): 1–35.
|
Farahani, R.Z., M. SteadieSeifi, and N. Asgari. 2010. Multiple criteria facility location problems: A survey. Applied Mathematical Modelling 34(7): 1689–1709.
|
Geng, J., H. Hou, and S. Geng. 2021. Optimization of warehouse location and supplies allocation for emergency rescue under joint government-enterprise cooperation considering disaster victims’ distress perception. Sustainability 13(19): Article 10560.
|
Guan, X.J., H. Zhou, M.X. Li, L.G. Zhou, and H.Y. Chen. 2021. Multilevel coverage location model of earthquake relief material storage repository considering distribution time sequence characteristics. Journal of Traffic and Transportation Engineering (English Edition) 8(2): 209–224.
|
Guo, D., J. Li, X. Li, Z. Li, P. Li, and Z. Chen. 2022. Advance prediction of collapse for TBM tunneling using deep learning method. Engineering Geology 299: Article 106556.
|
Hajipour, V., P. Fattahi, H. Bagheri, and S.B. Morad. 2022. Dynamic maximal covering location problem for fire stations under uncertainty: Soft-computing approaches. International Journal of System Assurance Engineering and Management 13(1): 90–112.
|
Jalali, S., M. Seifbarghy, J. Sadeghi, and S. Ahmadi. 2016. Optimizing a bi-objective reliable facility location problem with adapted stochastic measures using tuned-parameter multi-objective algorithms. Knowledge-Based Systems 95: 45–57.
|
Karatas, M. 2017. A multi-objective facility location problem in the presence of variable gradual coverage performance and cooperative cover. European Journal of Operational Research 262(3): 1040–1051.
|
Kılcı, F., B.Y. Kara, and B. Bozkaya. 2015. Locating temporary shelter areas after an earthquake: A case for Turkey. European Journal of Operational Research 243(1): 323–332.
|
Kim, J., C. Kim, G. Kim, I. Kim, Q. Abbas, and J. Lee. 2021. Probabilistic tunnel collapse risk evaluation model using analytical hierarchy process (AHP) and Delphi survey technique. Tunnelling and Underground Space Technology 120: Article 104262.
|
Küçükaydın, H., and N. Aras. 2020. Gradual covering location problem with multi-type facilities considering customer preferences. Computers and Industrial Engineering 147: Article 106577.
|
Li, X., J.X. Li, H.J. Cui, and M.Q. Zhu. 2021. Research on hierarchical scheduling of emergency resources for tunnel collapse based on demand time. Journal of Safety Science and Technology 17(1): 136–142 (in Chinese).
|
Li, Y.C., Y.D. Xue, and Y.J. Li. 2017. A new construction risk assessment method based on dynamic weight. Chinese Journal of Underground Space and Engineering 13(S1): 209–215 (in Chinese).
|
Liu, Y., Y. Yuan, J.Y. Shen, and W. Gao. 2021. Emergency response facility location in transportation networks: A literature review. Journal of Traffic and Transportation Engineering (English Edition) 8(2): 153–169.
|
Lu, X.L., and Y.X. Hou. 2010. Allocation of Chinese national emergency material depository based on facility location theory. Economic Geography 30(7): 1091–1095 (in Chinese).
|
von Lücken, C., B. Barán, and C. Brizuela. 2014. A survey on multi-objective evolutionary algorithms for many-objective problems. Computational Optimization and Applications 58(3): 707–756.
|
Ma, Y.J., W. Xu, L.J. Qin, X.J. Zhao, and J. Du. 2019. Hierarchical supplement location-allocation optimization for disaster supply warehouses in the Beijing-Tianjin-Hebei region of China. Geomatics, Natural Hazards and Risk 10(1): 102–117.
|
Meng, G., J. Liu, W. Qiu, B. Wu, and S. Xu. 2022. A failure probability evaluation method for the collapse of drill-blast tunnels based on a multistate cloud Bayesian network. Frontiers in Earth Science. https://doi.org/10.3389/feart.2022.856701.
|
Mestre, A.M., M.D. Oliveira, and A.P. Barbosa-Póvoa. 2015. Location–allocation approaches for hospital network planning under uncertainty. European Journal of Operational Research 240(3): 791–806.
|
Ministry of Construction of the People’s Republic of China. 2009. Code for investigation of geotechnical engineering (GB 50021–2001). Beijing: China Architecture & Building Press (in Chinese).
|
Ministry of Transport of the People’s Republic of China, Engineering Quality Supervision Bureau. 2011. Analysis of safety risk assessment system and guide for highway bridge and tunnel construction. Beijing: China Communication Press (in Chinese).
|
Mrkela, L., and Z. Stanimirović. 2022. A Multi-objective variable neighborhood search for the maximal covering location problem with customer preferences. Cluster Computing 25(3): 1677–1693.
|
Mukhopadhyay, A., V. Yevgeniy, D. Abhishek, and G. Biswas. 2017. Prioritized allocation of emergency responders based on a continuous-time incident prediction model. In Proceedings of the 16th International Conference on Autonomous Agents and Multi Agent Systems, 8–12 May 2017, São Paulo, Brazil, 168–177.
|
Oksuz, M.K., and S.I. Satoglu. 2019. A two-stage stochastic model for location planning of temporary medical centers for disaster response. International Journal of Disaster Risk Reduction 44: Article 101426.
|
Ou, G.-Z., Y.-Y. Jiao, G.-H. Zhang, J.-P. Zou, F. Tan, and W.-S. Zhang. 2021. Collapse risk assessment of deep-buried tunnel during construction and its application. Tunnelling and Underground Space Technology 115: Article 104019.
|
Rauchecker, G., and G. Schryen. 2019. An exact branch-and-price algorithm for scheduling rescue units during disaster response. European Journal of Operational Research 272(1): 352–363.
|
Ren, X.Y., and J. Tan. 2022. Location allocation collaborative optimization of emergency temporary distribution center under uncertainties. Mathematical Problems in Engineering. https://doi.org/10.1155/2022/6176756.
|
Shaw, L., S.K. Das, and S.K. Roy. 2022. Location-allocation problem for resource distribution under uncertainty in disaster relief operations. Socio-Economic Planning Sciences 82(Part A): Article 101232.
|
State Council of the people’s Republic of China. 2017. National comprehensive disaster prevention and reduction plan (2016–2020). http://www.gov.cn/zhengce/content/2017-01/13/content_5159459.htm. Accessed 13 Jan 2017 (in Chinese).
|
Sun, Y.N., Y.H. Wang, and J.H. Liao. 2010. Preliminary study of demand model of disaster relief and its index system and aid assessment. Research on Economics and Management 6: 85–94 (in Chinese).
|
Tang, Z.P., J. Qin, J.P. Sun, and F. Niu. 2018. Multi-objective optimization method for dispatching of railway emergency resources under uncertainty conditions. Journal of the China Railway Society 40(1): 9–16 (in Chinese).
|
Toregas, C., R. Swain, C. ReVelle, and L. Bergman. 1971. The location of emergency service facilities. Operations Research 19(6): 1363–1373.
|
Trivedi, A., and A. Singh. 2017. A hybrid multi-objective decision model for emergency shelter location-relocation projects using fuzzy analytic hierarchy process and goal programming approach. International Journal of Project Management 35(5): 827–840.
|
Vahdani, B., D. Veysmoradi, F. Noori, and F. Mansour. 2018. Two-stage multi-objective location-routing-inventory model for humanitarian logistics network design under uncertainty. International Journal of Disaster Risk Reduction 27: 290–306.
|
Wang, Y.Y. 2021. Multiperiod optimal allocation of emergency resources in support of cross-regional disaster sustainable rescue. International Journal of Disaster Risk Science 12(3): 394–409.
|
Xu, W., Y. Ma, X. Zhao, Y. Li, L. Qin, and J. Du. 2017. A comparison of scenario-based hybrid bilevel and multi-objective location-allocation models for earthquake emergency shelters: A case study in the central area of Beijing, China. International Journal of Geographical Information Science 32(2): 236–256.
|
Xu, W., X. Zhao, Y. Ma, Y. Li, L. Qin, Y. Wang, and J. Du. 2018. A multi-objective optimization based method for evaluating earthquake shelter location–allocation. Geomatics, Natural Hazards and Risk 9(1): 662–677.
|
Xu, Z., N. Cai, X. Li, M. Xian, and T. Dong. 2021. Risk assessment of loess tunnel collapse during construction based on an attribute recognition model. Bulletin of Engineering Geology and the Environment 80(8): 6205–6220.
|
Yenice, Z.D., and F. Samanlioglu. 2020. A multi-objective stochastic model for an earthquake relief network. Journal of Advanced Transportation. https://doi.org/10.1155/2020/1910632.
|
Yushimito, W.F., M. Jaller, and S. Ukkusuri. 2012. A Voronoi-based heuristic algorithm for locating distribution centers in disasters. Networks and Spatial Economics 12(1): 21–39.
|
Zhang, J., M. Dong, and F. Chen. 2013. A bottleneck Steiner tree based multi-objective location model and intelligent optimization of emergency logistics systems. Robotics and Computer-Integrated Manufacturing 29(3): 48–55.
|
Zhao, M., and Q.W. Chen. 2015. Risk-based optimization of emergency rescue facilities locations for large-scale environmental accidents to improve urban public safety. Natural Hazards 75(1): 163–189.
|
Zhao, X., W. Xu, Y. Ma, L. Qin, J. Zhang, and Y. Wang. 2017. Relationships between evacuation population size, earthquake emergency shelter capacity, and evacuation time. International Journal of Disaster Risk Science 8(4): 457–470.
|