Afshar A. and Haghani A. (2012). Modeling integrated supply chain logistics in real-time large-scale disaster relief operations. Socio-Economic Planning Sciences, Vol. 46(4), pp. 327-338.
Ahmadi M., Seifi A. and Tootooni B. (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, Vol. 75, pp. 145-163.
Alinaghian M., Aghaie M. and Sabbagh M. S. (2019). A mathematical model for location of temporary relief centers and dynamic routing of aerial rescue vehicles. Computers & Industrial Engineering, Vol. 131, pp. 227–241.
Al-Theeb N. and Murray C. (2017). Vehicle routing and resource distribution in post disaster humanitarian relief operations. International Transactions in Operational Research,Vol. 24(6), pp. 1253-1284.
Balcik B., Beamon B. and Smilowitz K. (2008). Last mile distribution in humanitarian relief. Journal of Intelligent Transportation Systems, Vol. 12(2), pp. 51-63.
Ben-Tal A., El-Ghaoui L. and Nemirovski A. (2009). Robust Optimization, Princeton University Press.
Bozorgi-Amiri A., Jabalameli M. S. and Mirzapour Al-e-Hashem S. M. J. (2013). A multi-objective robust stochastic programming model for disaster relief logistics under uncertainty. OR Spectrum, Vol. 35(4), pp. 905–933.
Bozorgi-Amiri A., and Khorsi M. (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, Vol. 85(5), pp. 1633–1648.
Çankaya E., Ekici A. and Özener O.Ö. (2019). Humanitarian relief supplies distribution: an application of inventory routing problem. Annals of Operations Research, Vol. 283, pp. 119–141.
Dantzig G.B. and Ramser J.H. (1959). The truck dispatching problem. Management Science, Vol. 6(1), pp. 80–91.
Davoodi S. M. R. and Goli A. (2019). An integrated disaster relief model based on covering tour using hybrid Benders decomposition and variable neighborhood search: Application in the Iranian context. Computers & Industrial Engineering, Vol. 130, pp. 370-380.
Ekici A. and Özener O.Ö. (2020). Inventory routing for the last mile delivery of humanitarian relief supplies. OR Spectrum, Vol. 42, pp. 621–660.
Ghasemi P., Khalili-DamghaniK., HafezalkotobA. andRaissi S. (2020). Stochastic optimization model for distribution and evacuation planning (A case study of Tehran earthquake). Socio-Economic Planning Sciences, Vol. 71, pp.100745.
Goli A. and Malmir B. (2020). A Covering Tour Approach for Disaster Relief Locating and Routing with Fuzzy Demand. International Journal of Intelligent Transportation Systems Research,https://doi.org/10.1007/s13177-019-00185-2.
Haghani A. and Oh S. C. (1996). Formulation and solution of a multi-commodity, multi-modal network flow model for disaster relief operations. Transportation Research Part A: Policy and Practice, Vol. 30(3), pp. 231-250.
Haghi M., Fatemi Ghomi S. M. T. and Jolai F. (2017). Developing a robust multi-objective model for pre/post disaster times under uncertainty in demand and resource. Journal of Cleaner Production, Vol. 154, pp. 188-202.
Huang M., Smilowitz K. and Balcik B. (2011). Models for relief routing: Equity, efficiency and efficacy. Procedia - Social and Behavioral Sciences, Vol. 17, pp. 416–437.
Jiménez M., Arenas M., Bilbao A. and Rodriguez M.V. (2007). Linear programming with fuzzy parameters: An interactive method resolution. European Journal of Operational Research, Vol. 177(3), pp. 1599–1609.
Li Y. and Chung S. H. (2019). Disaster Relief Routing Under Uncertainty: A Robust Optimization Approach. IISE Transactions, doi: https://doi.org/10.1080/24725854.2018.1450540.
Lin Y.H., Batta R., Rogerson P., Blatt A. and Flanigan M. (2011). A logistics model for emergency supply of critical items in the aftermath of a disaster. Socio-Economic Planning Sciences, Vol. 45(4), pp. 132-145.
Maghfiroh M.F.N. and Hanaoka S. (2018). Dynamic truck and trailer routing problem for last mile distribution in disaster response. Journal of Humanitarian Logistics and Supply Chain Management, Vol. 8(2), pp. 252-278.
Mamashli Z., Bozorgi-Amiri A., Dadashpour I., Nayeri S. and Heydari J. (2021). A heuristic-based multi-choice goal programming for the stochastic sustainable-resilient routing-allocation problem in relief logistics. Neural Computing and Applications, Vol. 33(21), pp. 14283-14309.
Mete O. N. and Zabinsky Z. (2009). Stochastic optimization of medical supply location and distribution in disaster. International Journal of Production Economics, Vol. 126(1), pp. 76-84.
Mohamadi A., Yaghoubi S. and Pishvaee M.S. (2017). Fuzzy multi-objective stochastic programming model for disaster relief logistics considering telecommunication infrastructures: a case study. Operational Research an International Journal, Vol. 19, pp. 59–99.
Mohammadi S., Darestani S.A., Vahdani B. and Alinezhad A. (2020). A Robust Neutrosophic Fuzzy-based Approach to Integrate Reliable Facility Location and Routing Decisions for Disaster Relief under Fairness and Aftershocks Concerns.
Computers & Industrial Engineering, doi:
https://doi.org/10.1016/j.cie.2020.106734.
Mula J., Poler R. and Garcia J.P. (2006). MRP with flexible constraints: A fuzzy mathematical programming approach. Fuzzy Sets and Systems, Vol. 157(1), pp. pp. 74–97.
Najafi M., Eshghi K. and Dullaert W. (2013). A multi-objective robust optimization model for logistics planning in the earthquake response phase. Transportation Research Part E: Logistics and Transportation Review, Vol. 49, pp. 217–249.
Nodoust S., Pishvaee M.S. and Seyedhosseini S.M. (2021). Vehicle routing problem for humanitarian relief distribution under hybrid uncertainty. Kybernetes, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/K-09-2021-0839.
Ozdamar L. and Demir O. (2012). A hierarchical clustering and routing procedure for large scale disaster relief logistics planning. Transportation Research Part E: Logistics and Transportation Review, Vol. 48(3), pp. 591-602.
Ozdamar L., Ekinci E. and Kucukyazici B. (2004). Emergency logistics planning in natural disasters. Annals of Operations Research, Vol. 129, pp. 217-245.
Ozdamar L. and Ertem M. (2015). Models, solutions and enabling technologies in humanitarian logistics. European Journal of Operations Research, Vol. 244, pp. 55-65.
Pishvaee M.S. and Fazli Khalaf M. (2016). Novel robust fuzzy mathematical programming methods. Applied Mathematical Modelling, Vol. 40(1), pp. 407–418.
Pishvaee M. S. and Torabi S. A. (2010). A possibilistic programming approach for closed-loop supply chain network design under uncertainty. Fuzzy Sets and Systems, Vol. 161, pp. 2668-2683.
Pishvaee M. S., Torabi S. A. and Razmi J. (2012). Credibility-based fuzzy mathematical programming model for green logistics design under uncertainty. Computers and Industrial Engineering, Vol. 62, pp. 624-632.
Rabbani M., Akbarpour M., Hosseini M. and Farrokhi-Asl H. (2021). A Multi-Depot Vehicle Routing Problem with Time Windows and Load Balancing: A Real World Application. International Journal of Supply and Operations Management, Vol. 8(3), pp. 347–369.
Rath S. and Gutjahr W.J. (2014). A math-heuristic for the warehouse location–routing problem in disaster relief. Computers & Operations Research, Vol. 42, pp. 25–39.
Rennemo S. J., Rø K. F., Hvattum L. M. and Tirado G. (2014). A three-stage stochastic facility routing model for disaster response planning. Transportation Research Part E: Logistics and Transportation Review, Vol. 62, pp. 116-135.
Rezaei-Malek M., Tavakkoli-Moghaddam R., Zahiri B. and Bozorgi-Amiri A. (2016). An Interactive Approach for Designing a Robust Disaster Relief Logistics Network with Perishable Commodities. Computers & Industrial Engineering, Vol. 94, pp. 201–215.
Sabouhi F., Bozorgi-Amiri A. and Vaez P. (2021). Stochastic optimization for transportation planning in disaster relief under disruption and uncertainty. Kybernetes, Vol. 50(9), pp. 2632-2650.
Safaei A. S., Farsad S. and Paydar M. M. (2018). Robust bi-level optimization of relief logistics operations. Applied Mathematical Modelling, Vol. 56, pp. 359–380.
Sakiani R., Seifi A. and Khorshiddoust R.R. (2020). Inventory routing and dynamic redistribution of relief goods in post-disaster operations. Computers and Industrial Engineering, Vol. 140, https://doi.org/10.1016/j.cie.2019.106219.
Tang C.S. (2006). Robust strategies for mitigating supply chain disruptions. International Journal of Logistics Research and Applications, Vol. 9(1), pp. 33-45.
Tavana M., Abtahi A. R., Caprio D. D., Hashemi R. and Yousefi-Zenouz R. (2018). An integrated location-inventory-routing humanitarian supply chain network with pre- and post-disaster management considerations. Socio-Economic Planning Sciences, Vol. 64, pp. 21-37.
Tofighi S., Torabi S. A. and Mansouri S. A. (2016). Humanitarian logistics network design under mixed uncertainty. European Journal of Operations Research, Vol. 250(1), pp. 239-250.
Vahdani B., Veysmoradi D., Mousavi S. M. and Amiri M. (2021). Planning for relief distribution, victim evacuation, redistricting and service sharing under uncertainty. Socio-Economic Planning Sciences, 101158.
Vahdani B., Veysmoradi D., Shekari N. and Mousavi S. M. (2018). Multi-objective, multi period location-routing model to distribute relief after earthquake by considering emergency roadway repair.
Neural Computing and Applications, Vol. 30, pp. 835-854.
Villarreal B., Garza-Reyes J.A., Kumar V. and Lim M.K. (2016). Improving road transport operations through lean thinking: A case study. International Journal of Logistics, Vol. 20(2), pp. 163-180.
Wei X., Qiu H., Wang D., Duan J., Wang Y. and Cheng T. C. E. (2020). An integrated location routing problem with post-disaster relief distribution. Computers and Industrial Engineering, Vol. 147, https://doi.org/10.1016/j.cie.2020.106632.
Yi W. and Özdamar L. (2007). A dynamic logistics coordination model for evacuation and support in disaster response activities. European Journal of Operations Research, Vol. 179(3), pp. 1177-1193.
Yu G. and Yang Y. (2019). Dynamic routing with real-time traffic information. Operational Research, Vol. 19(6), pp. 1033–1058.
Zhong Sh., Cheng R., Jiang Y., Wang Zh., Larsen A. and Nielsen O. A. (2020). Risk-averse optimization of disaster relief facility location and vehicle routing under stochastic demand. Transportation Research Part E: Logistics and Transportation Review, Vol. 141, 102015, https://doi.org/10.1016/j.tre.2020.102015.