- حسینینژاد، س.ف.، ماکویی، ا. و توکلیمقدم، ر.، (1397)، "مدلسازی مکانیابی هاب زنجیره امدادرسانی در مدیریت بحران بر مبنای نیاز مصدومین تصادفات جادهای" پژوهشنامه حمل و نقل، دوره پانزدهم، شمار سوم، ص. 321-335.
-Burak, Kõ., Yetis- Kara, B., Saldanha-da-Gama, F. and Correia, I., (2019), “Modeling the shelter site location problem using chance constraints: A case study for Istanbul”, European Journal of Operational Research, Vol.270, No.1, pp. 132-145.
- 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.
-Diabat, A., Jabbarzadeh, A. and Khosrojerdi, A., (2019), “A perishable product supply chain network design problem with reliability and disruption considerations”, International Journal of Production Economics,
Vol. 212,
pp. 125-138.
-Golabi, M., Shavarani, S.M. & Izbirak, G., (2017), “An edge-based stochastic facility location problem in UAV-supported humanitarian relief logistics: a case, study of Tehran earthquake,
Natural Hazards”, Vol.87, No.3, pp. 1545–1565.
-Jafarkhan, F. and Yaghoubi, S., (2019), “An efficient solution method for the flexible and robust inventory-routing of red blood cells”, Computers & Industrial Engineering, vol.117, pp.191-206.
-Karimkashi, S. & Kishk, A. A., (2010), “Invasive weed optimization and its features in electromagnetics”, IEEE transactions on antennas and propagation, vol.58, No.4, pp.1269-1278.
-Karaoğlan, I., Erdoğan, G. and Koç, Ç., (2018), “The Multi-Vehicle Probabilistic Covering Tour Problem”, European Journal of Operational Research, Vol.271, No.1, pp.278-287.
-Mavrotas, G., (2009), “Effective implementation of the ε-constraint method in multi-objective mathematical programming problems”, Applied mathematics and computation, Vol. 213, pp.455-465.
-Mehrabian, A. R. and Lucas, C., (2006), “A novel numerical optimization algorithm inspired from weed colonization”, Ecological informatics , Vol.1, No.4, pp. 355-366.
-Moreno, A., Alem, D., Ferreira, D. and Clark, a., (2018), “A mathematical model for efficient emergency transportation in a disaster situation”, American Journal of Emergency Medicine, Vol.36, No.9, pp. 1585-1590.
-Nathalie, C. and Victor, C., (2019), “Including deprivation costs in facility location models for humanitarian relief logistics”, Socio-Economic Planning Sciences, Vol.65, pp. 89–100.
-Ni, W., Shu, J. and Song, M., (2018), “Location and Emergency Inventory Pre-Positioning for Disaster Response Operations: Min-Max Robust Model and a Case Study of Yushu Earthquake”, Production and Operation Management; Vol.27, No.1, pp.160–183.
-Nikoo, N., Babaei, M. and Shariat-Mohaymany, A., (2018), “Emergency Transportation Network Design Problem: Identification and Evaluation of Disaster Response Routes”, International Journal of Disaster RiskReduction, vol.27, pp.7-20.
-Tavana, M., Abtahi, A.R, Di Caprio, 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.
-Taguchi, G., Chowdhury, S. and Wu, Y. (2005), "Taguchi’s quality engineering handbook", Wiley Publishing.
-Tavakkoli-Moghaddam, R. and Raziei, Z. (2016), “A New Bi-Objective Location-Routing-Inventory Problem with Fuzzy Demands”, IFAC, Vol.49, No.12, pp.1116 –1121.
-“The Study on Seismic Microzoning of the Greater Tehran Area in the Islamic Republic of Iran”, (2000). Japan International Cooperation Agency (JICA).
-Zokaee, S., Bozorgi-Amiri, A. and Sadjadi, S.J. (2016), “A Robust Optimization Model for Humanitarian Relief Chain Design under Uncertainty”, Applied Mathematical Modelling, Vol.40, No.17–18, pp.7996-8016.