1. Abounacer, R., Rekik, M., & Renaud, J. (2014). An exact solution approach for multi-objective location–transportation problem for disaster response. Computers & Operations Research, 41, 83-93.
2. An, S., Cui, N., Li, X., & Ouyang, Y. (2013). Location planning for transit-based evacuation under the risk of service disruptions. Transportation Research Part B: Methodological, 54, 1-16.
3. Barzinpour, F., & Esmaeili, V. (2014). A multi-objective relief chain location distribution model for urban disaster management. The International Journal of Advanced Manufacturing Technology, 70(5-8), 1291-1302.
4. Ben-Tal, A., & Nemirovski, A. (2008). Selected topics in robust convex optimization. Mathematical Programming, 112(1), 125-158.
5. Bertsimas, D., & Sim, M. (2004). The price of robustness. Operations research, 52(1), 35-53.
6. Bozorgi-Amiri, A., Jabalameli, M. S., & Al-e-Hashem, S. M. (2013). A multi-objective robust stochastic programming model for disaster relief logistics under uncertainty. OR spectrum, 35(4), 905-933.
7. Caunhye, A. M., Nie, X., & Pokharel, S. (2012). Optimization models in emergency logistics: A literature review. Socio-economic planning sciences, 46(1), 4-13.
8. Das, R., & HANAOKA, S. (2013). Robust network design with supply and demand uncertainties in humanitarian logistics. Journal of the Eastern Asia Society for Transportation Studies, 10(0), 954-969.
9. De Brito Junior, I., Leiras, A., & Yoshizaki, H. T. Y. (2013). Stochastic optimization applied to the prepositioning of disaster relief supply decisions in Brazil.
10. Döyen, A., Aras, N., & Barbarosoğlu, G. (2012). A two-echelon stochastic facility location model for humanitarian relief logistics. Optimization Letters,6(6), 1123-1145.
11. Gama, M., Santos, B. F., & Scaparra, M. P. (2015). A multi-period shelter location-allocation model with evacuation orders for flood disasters. EURO Journal on Computational Optimization, 1-25.
12. Gonçalves, P., Leiras, A., & Chawaguta, B. Stochastic Optimization for Humanitarian Aid Supply and Distribution of World Food Programme (WFP) in Ethiopia
13. Guan, J. (2014). Emergency Rescue Location Model with Uncertain Rescue Time. Mathematical Problems in Engineering, 2014.
14. Kalantari, M., Pishvaee, MS., & Yaghoubi, S.,(2015)., A Multi Objective Model Integrating Financial and Material Flow in Supply Chain Master Planning, Journal of Industrial Management Perspective, 19, 9-31 (In Persian)
15. Kulshrestha, A., Lou, Y., & Yin, Y. (2014). Pick‐up locations and bus allocation for transit‐based evacuation planning with demand uncertainty. Journal of Advanced Transportation, 48(7), 721-733.
16. Liu, C. H., & Tsai, W. N. (2015). Multi-objective parallel machine scheduling problems by considering controllable processing times. Journal of the Operational Research Society, 67(4), 654-663.
17. Rawls, C. G., & Turnquist, M. A. (2010). Pre-positioning of emergency supplies for disaster response. Transportation research part B: Methodological, 44(4), 521-534.
18. Rahimi, H., Azar, A., & Rezaei Pandari, A., (2015).,Designing a Multi Objective Job Shop Scheduling Model and Solving it by Simulated Annealing, Journal of Industrial Management Perspective, 1, 57-77 (In Persian)
19. Rennemo, S. J., Rø, K. F., Hvattum, L. M., & Tirado, G. (2014). A three-stage stochastic facility routing model for disaster response planning. Transportation research part E: logistics and transportation review, 62, 116-135.
20. Rezaei-Malek, M., & Tavakkoli-Moghaddam, R. (2014). Robust humanitarian relief logistics network plnning. Uncertain Supply Chain Management, 2(2), 73-96.
21. Shahbandarzadeh, H., & Paykam, A., (2015).,Employment of a Weighted Fuzzy Multi-Objective Programming Model to Determine the Amount of Optimum Purchasing from Suppliers, Journal of Industrial Management Perspective, 18, 129-152 (In Persian).
22. Sheu, J. B., & Pan, C. (2015). Relief supply collaboration for emergency logistics responses to large-scale disasters. Transportmetrica A: Transport Science, 11(3), 210-242.
23. Zokaee, S., Bozorgi-Amiri, A., & Sadjadi, S. J. (2016). A Robust Optimization Model for Humanitarian Relief Chain Design under Uncertainty. Applied Mathematical Modelling.
24. Wang, H., Du, L., & Ma, S. (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, 160-179.
25. Özdamar, L., & Ertem, M. A. (2015). Models, solutions and enabling technologies in humanitarian logistics. European Journal of Operational Research, 244(1), 55-6.