Multi-commodity rebalancing and transportation planning considering traffic congestion and uncertainties in disaster response

Altay, 2006, OR/MS research in disaster operations management, European Journal of Operational Research, 175, 475, 10.1016/j.ejor.2005.05.016 Arnette, 2019, A Risk-Based Approach to Improving Disaster Relief Asset Pre-Positioning, Production and Operations Management, 28, 457, 10.1111/poms.12934 Bababeik, 2018, Increasing the resilience level of a vulnerable rail network: The strategy of location and allocation of emergency relief trains, Transportation Research Part E: Logistics and Transportation Review, 119, 110, 10.1016/j.tre.2018.09.009 Baharmand, 2019, Bi-objective multi-layer location–allocation model for the immediate aftermath of sudden-onset disasters, Transportation Research Part E: Logistics and Transportation Review, 127, 86, 10.1016/j.tre.2019.05.002 Bai, X. (2016). Two-stage multiobjective optimization for emergency supplies allocation problem under integrated uncertainty, Mathematical Problems in Engineering. 2016. Balcik, 2019, Collaborative Prepositioning Network Design for Regional Disaster Response, Production and Operations Management, 28, 2431, 10.1111/poms.13053 Bozorgi-Amiri, 2013, A multi-objective robust stochastic programming model for disaster relief logistics under uncertainty, OR Spectrum, 35, 905, 10.1007/s00291-011-0268-x BPR, U.S. (1964). Traffic assignment manual for application with a large, high speed computer (US Department of Commerce, Bureau of Public Roads, Office of Planning, Urban Planning Division). Camacho-Vallejo, 2015, A bi-level optimization model for aid distribution after the occurrence of a disaster, Journal of Cleaner Production, 105, 134, 10.1016/j.jclepro.2014.09.069 Campos, 2012, A method for evacuation route planning in disaster situations, Procedia-Social and Behavioral Sciences, 54, 503, 10.1016/j.sbspro.2012.09.768 Cao, 2018, A novel multi-objective programming model of relief distribution for sustainable disaster supply chain in large-scale natural disasters, Journal of Cleaner Production, 174, 1422, 10.1016/j.jclepro.2017.11.037 Caunhye, 2012, Optimization models in emergency logistics: A literature review, Socio-economic Planning Sciences, 46, 4, 10.1016/j.seps.2011.04.004 Cavdur, 2016, Allocation of temporary disaster response facilities under demand uncertainty: An earthquake case study, International Journal of Disaster Risk Reduction, 19, 159, 10.1016/j.ijdrr.2016.08.009 Chankong, 2008 Chen, 2016, Network based temporary facility location for the Emergency Medical Services considering the disaster induced demand and the transportation infrastructure in disaster response, Transportation Research Part B: Methodological, 91, 408, 10.1016/j.trb.2016.06.004 Chiu, 2007, Real-time mobilization decisions for multi-priority emergency response resources and evacuation groups: Model formulation and solution, Transportation Research Part E: Logistics and Transportation Review, 43, 710, 10.1016/j.tre.2006.11.006 Clark, 2013, A network transshipment model for planning humanitarian relief operations after a natural disaster, Decision Aid Models for Disaster Management and Emergencies, Atlantis Computational Intelligence Systems, 7, 233, 10.2991/978-94-91216-74-9_11 Dai, 2017, A two-stage approach for bi-objective integer linear programming, Operations Research Letters Davis, 2013, Inventory planning and coordination in disaster relief efforts, International Journal of Production Economics, 141, 561, 10.1016/j.ijpe.2012.09.012 Döyen, 2012, A two-echelon stochastic facility location model for humanitarian relief logistics, Optimization Letters, 6, 1123, 10.1007/s11590-011-0421-0 Dubey, 2019, Disaster relief operations: Past, present and future, Annals of Operations Research, 1, 10.1007/s10479-019-03440-7 Elci, 2018, A chance-constrained two-stage stochastic programming model for humanitarian relief network design, Transportation Research Part B-Methodological, 108, 55, 10.1016/j.trb.2017.12.002 Erbeyoğlu, 2020, A robust disaster preparedness model for effective and fair disaster response, European Journal of Operational Research, 280, 479, 10.1016/j.ejor.2019.07.029 Florian, M.A., (1974). Traffic equilibrium methods, Lecture notes in economics and mathematical systems. 118. Galindo, 2013, Review of recent developments in OR/MS research in disaster operations management, European Journal of Operational Research, 230, 201, 10.1016/j.ejor.2013.01.039 Gao, X. (2019a). A Bi-Level Stochastic Optimization Model for Commodity Rebalancing in Humanitarian Operations. In Proceedings of international conference on computers and industrial engineering, CIE. Beijing, China. Gao, X. (2019b). A Stochastic Optimization Model for Commodity Rebalancing Under Traffic Congestion in Disaster Response. In IFIP International Conference on Advances in Production Management Systems, 91-99. Springer. Gao, 2020, A bi-level stochastic optimization model for multi-commodity rebalancing under uncertainty in disaster response, Annals of Operations Research, 1 Gao, 2020, A novel multi-objective scenario-based optimization model for sustainable reverse logistics supply chain network redesign considering facility reconstruction, Journal of Cleaner Production, 122405 Gao, 2018, A Stochastic Programming Model for Multi-commodity Redistribution Planning in Disaster Response, 67 Gao, 2018, A two-stage stochastic programming model for commodity redistribution under uncertainty in disaster response Gao, 2019, A robust two-stage transit-based evacuation model for large-scale disaster response, Measurement, 145, 713, 10.1016/j.measurement.2019.05.067 Gao, 2017, A Hybrid Genetic Algorithm For Multi-emergency Medical Service Center Location-allocation Problem In Disaster Response, International Journal of Industrial Engineering, 24 Gilbert, P. (2016). Human nature and suffering (Taylor & Francis Ltd, Routledge: London, United Kingdom). Gutjahr, 2016, Bi-objective bilevel optimization of distribution center locations considering user equilibria, Transportation Research Part E: Logistics and Transportation Review, 85, 1, 10.1016/j.tre.2015.11.001 Haddow, G., J. Bullock, and D.P. Coppola. (2017). Introduction to emergency management (Butterworth-Heinemann). Haghi, 2017, Developing a robust multi-objective model for pre/post disaster times under uncertainty in demand and resource, Journal of Cleaner Production, 154, 188, 10.1016/j.jclepro.2017.03.102 Haimes, 1971, On a bicriterion formulation of the problems of integrated system identification and system optimization, IEEE transactions on systems, man, and cybernetics, 1, 296 Holguín-Veras, 2013, On the appropriate objective function for post-disaster humanitarian logistics models, Journal of Operations Management, 31, 262, 10.1016/j.jom.2013.06.002 Hong, 2015, Stochastic network design for disaster preparedness, IIE Transactions, 47, 329, 10.1080/0740817X.2014.919044 Jia, 2007, Solution approaches for facility location of medical supplies for large-scale emergencies, Computers & Industrial Engineering, 52, 257, 10.1016/j.cie.2006.12.007 Jotshi, 2009, Dispatching and routing of emergency vehicles in disaster mitigation using data fusion, Socio-Economic Planning Sciences, 43, 1, 10.1016/j.seps.2008.02.005 Kirac, 2015, The traveling salesman problem with imperfect information with application in disaster relief tour planning, IIE Transactions, 47, 783, 10.1080/0740817X.2014.976351 Li, 2017, Integrating uncertain user-generated demand data when locating facilities for disaster response commodity distribution, Socio-Economic Planning Sciences Li, 2011, Sheltering network planning and management with a case in the Gulf Coast region, International Journal of Production Economics, 131, 431, 10.1016/j.ijpe.2010.12.013 Lin, 2011, A logistics model for emergency supply of critical items in the aftermath of a disaster, Socio-Economic Planning Sciences, 45, 132, 10.1016/j.seps.2011.04.003 Liu, 2019, A robust model predictive control approach for post-disaster relief distribution, Computers & Industrial Engineering, 135, 1253, 10.1016/j.cie.2018.09.005 Loree, 2018, Points of distribution location and inventory management model for Post-Disaster Humanitarian Logistics, Transportation Research Part E: Logistics and Transportation Review, 116, 1, 10.1016/j.tre.2018.05.003 Manual, H.C. (2000). Highway capacity manual, Washington, DC. Mavrotas, 2009, Effective implementation of the ε-constraint method in multi-objective mathematical programming problems, Applied Mathematics and Computation, 213, 455, 10.1016/j.amc.2009.03.037 Mete, 2010, Stochastic optimization of medical supply location and distribution in disaster management, International Journal of Production Economics, 126, 76, 10.1016/j.ijpe.2009.10.004 Mills, 2018, Dynamic Distribution of Patients to Medical Facilities in the Aftermath of a Disaster, Operations Research, 66, 716, 10.1287/opre.2017.1695 Mohamadi, 2017, A bi-objective stochastic model for emergency medical services network design with backup services for disasters under disruptions: An earthquake case study, International Journal of Disaster Risk Reduction, 23, 204, 10.1016/j.ijdrr.2017.05.003 Mohammadi, 2016, Prepositioning emergency earthquake response supplies: A new multi-objective particle swarm optimization algorithm, Applied Mathematical Modelling, 40, 5183, 10.1016/j.apm.2015.10.022 Murali, 2012, Facility location under demand uncertainty: Response to a large-scale bio-terror attack, Socio-Economic Planning Sciences, 46, 78, 10.1016/j.seps.2011.09.001 Nagurney, 2016, A Generalized Nash Equilibrium network model for post-disaster humanitarian relief, Transportation Research Part E: Logistics and Transportation Review, 95, 1, 10.1016/j.tre.2016.08.005 Ni, 2018, Location and Emergency Inventory Pre-Positioning for Disaster Response Operations: Min-Max Robust Model and a Case Study of Yushu Earthquake, Production and Operations Management, 27, 160, 10.1111/poms.12789 Noyan, 2012, Risk-averse two-stage stochastic programming with an application to disaster management, Computers & Operations Research, 39, 541, 10.1016/j.cor.2011.03.017 Noyan, 2015, A stochastic optimization model for designing last mile relief networks, Transportation Science, 50, 1092, 10.1287/trsc.2015.0621 Pérez-Rodríguez, 2015, Inventory-allocation distribution models for postdisaster humanitarian logistics with explicit consideration of deprivation costs, Transportation Science, 50, 1261, 10.1287/trsc.2014.0565 Rath, 2016, Bi-objective stochastic programming models for determining depot locations in disaster relief operations, International Transactions in Operational Research, 23, 997, 10.1111/itor.12163 Rawls, 2010, Pre-positioning of emergency supplies for disaster response, Transportation Research Part B: Methodological, 44, 521, 10.1016/j.trb.2009.08.003 Rennemo, 2014, A three-stage stochastic facility routing model for disaster response planning, Transportation Research Part E: Logistics and Transportation Review, 62, 116, 10.1016/j.tre.2013.12.006 Rezaei-Malek, 2014, Robust humanitarian relief logistics network planning, Uncertain Supply Chain Management, 2, 73, 10.5267/j.uscm.2014.1.002 Rivera-Royero, 2016, A dynamic model for disaster response considering prioritized demand points, Socio-economic Planning Sciences, 55, 59, 10.1016/j.seps.2016.07.001 Rodríguez-Espíndola, 2018, Dynamic formulation for humanitarian response operations incorporating multiple organisations, International Journal of Production Economics, 204, 83, 10.1016/j.ijpe.2018.07.023 Rottkemper, 2012, A transshipment model for distribution and inventory relocation under uncertainty in humanitarian operations, Socio-Economic Planning Sciences, 46, 98, 10.1016/j.seps.2011.09.003 Safaei, 2018, Emergency logistics planning under supply risk and demand uncertainty, Operational Research, 1 Safaei, 2018, Robust bi-level optimization of relief logistics operations, Applied Mathematical Modelling, 56, 359, 10.1016/j.apm.2017.12.003 Sarma, 2019, A mathematical model for resource allocation in emergency situations with the co-operation of NGOs under uncertainty, Computers & Industrial Engineering, 137, 10.1016/j.cie.2019.106000 Sarma, 2020, An optimal redistribution plan considering aftermath disruption in disaster management, Soft Computing, 24, 65, 10.1007/s00500-019-04287-7 Sarma, 2020, Uncertain demand estimation with optimization of time and cost using Facebook disaster map in emergency relief operation, Applied Soft Computing, 87, 10.1016/j.asoc.2019.105992 Sarma, 2019, Redistribution for cost minimization in disaster management under uncertainty with trapezoidal neutrosophic number, Computers in Industry, 109, 226, 10.1016/j.compind.2019.04.004 Slim, 1997, Relief agencies and moral standing in war: Principles of humanity, neutrality, impartiality and solidarity1, Development in Practice, 7, 342, 10.1080/09614529754134 Starr, 2014, Introduction to the special issue on humanitarian operations and crisis management, Production and Operations Management, 23, 925, 10.1111/poms.12227 Stepanov, 2009, Multi-objective evacuation routing in transportation networks, European Journal of Operational Research, 198, 435, 10.1016/j.ejor.2008.08.025 Tofighi, 2016, Humanitarian logistics network design under mixed uncertainty, European Journal of Operational Research, 250, 239, 10.1016/j.ejor.2015.08.059 Tomasini, R., L. Van Wassenhove, and L. Van Wassenhove. (2009). Humanitarian logistics (Springer). Van Wassenhove, 2006, Humanitarian aid logistics: Supply chain management in high gear, Journal of the Operational research Society, 57, 475, 10.1057/palgrave.jors.2602125 Wang, 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, 69, 160, 10.1016/j.tre.2014.06.006 Wang, 2019, Augmenting fixed framework agreements in humanitarian logistics with a bonus contract, Production and Operations Management, 28, 1921, 10.1111/poms.13024 Wang, 2017, Estimation of deprivation level functions using a numerical rating scale, Production and Operations Management, 26, 2137, 10.1111/poms.12760 Wang, Y., and B. Sun. (2018). A Multiobjective Allocation Model for Emergency Resources That Balance Efficiency and Fairness, Mathematical Problems in Engineering. 2018. Weisbrod, G., D. Vary, and G. Treyz. (2001). Economic implications of congestion. Wen, 2014, Incorporating transportation network modeling tools within transportation economic impact studies of disasters, Journal of Traffic and Transportation Engineering (English edition), 1, 247, 10.1016/S2095-7564(15)30270-1 Zhou, 2017, A multi-objective evolutionary algorithm for multi-period dynamic emergency resource scheduling problems, Transportation Research Part E: Logistics and Transportation Review, 99, 77, 10.1016/j.tre.2016.12.011