[1] Parvaresh, F. Husseini, S. M. Golpayegany, S. H. & Karimi, B. (2014). Hub network design problem in the presence of disruptions, Journal of Intelligent Manufacturing, 25, 755-774.
[2] Sha, Y. and Huang, J. (2012). The multi-period location-allocation problem of engineering emergency blood supply systems, Systems Engineering Procedia, 5, 21-28.
[3] Sahin, G., Sural, H. and Meral, S. (2007). Locational analysis for regionalization of Turkish Red Crescent blood services, Computers & Operations Research, 34, 692-704.
[4] Cetin, E. and Sarul, L.S. (2009). A Blood Bank Location Model: A Multi-objective Approach, European Journal of Pure and Applied Mathematics, 2, 112-124.
[5] Nagurney, A. and Masoumi, A.H. (2012). Supply Chain Network Design of a Sustainable Blood Banking System, Sustainable Supply Chains. Springer New York, 174, 49-72.
[6] Arvan, M. Tavakkoli-Moghaddam, R. & Abdollahi, M. (2015). Designing a bi-objective and multi-product supply chain network for the supply of blood, Uncertain Supply Chain Management, 3, 57-68.
[7] Shariff, S.R., Moin, N.H. and Omar, M. (2012). Location allocation modeling for healthcare facility planning in Malaysia, Computers & Industrial Engineering, 62, 1000-1010.
[8] Araz, C., Selim, H. and Ozkarahan I. (2007). A fuzzy multi-objective covering-based vehicle location model for emergency services, Computers & Operations Research, 34, 705–726.
[9] Syam, S.S. and Cote, M. J. (2010). A location–allocation model for service providers with application to not-for-profit health care organizations, Omega, 38, 157-166.
[10] Doyen, A., Aras, N. and Barbarosoglu, G. (2012). A two-echelon stochastic facility location model for humanitarian relief logistics, Optimization Letter, 6, 1123-1145.
[11] Conbalat, M.S. and Massow, M.V. (2012). Locating emergency facilities with random demand for risk minimization, Expert Systems with Applications, 38, 10099-10106.
[12] Bozorgi-Amiri, A., Jabalameli, M.S. and Al-e-Hashem, S.M. (2013). A multi-objective robust stochastic programming model for disaster relief logistics under uncertainty, OR spectrum, 35, 905-933.
[13] Drezner, Z. (1978). Heuristic solution methods for two location problems with unreliable facilities, Journal of the Operational Research Society, 38, 509–514.
[14] Snyder, L.V. and Daskin, M.S. (2005). Reliability models for facility location: The expected failure cost case, Transportation Science, 39, 400–416.
[15] Berman, O., Krass, D. and Menezes, M.B.C. (2007). Facility reliability issues in network p-median problems: Strategic centralization and co-location effects, Operations Research, 55, 332–350.
[16] Berman, O., Drezner, T., Drezner, Z.and Wesolowsky, G.O. (2009). A defensive maximal covering problem on a network, International Transaction in Operational Research, 16, 69–86.
[17] Hong, J., Xie, Y. and Jeong, K. (2012). Development and evaluation of an integrated emergency response facility location model, Journal of Industrial Engineering and Management, 5, 4–21.
[18] Losada, C., Scaparra, M.P. and O’Hanley, J.R. (2012). Optimizing system resilience: A facility protection model with recovery time, European Journal of Operational Research, 217, 519–530.
[19] Liberatore, F., Scaparra, M.P. and Daskin, M.S. (2012). Hedging against disruptions with ripple effects in location analysis, Omega, 40, 21– 30.
[20] An, Y., Zeng, B., Zhang, Y., and Zhao, L. (2014). Reliable p-median facility location problem: two-stage robust models and algorithms. Transportation Research Part B: Methodological, 64, 54-72.
[21] Jabbarzadeh, A., Fahimnia, B., and Seuring, S. (2014). Dynamic supply chain network design for the supply of blood in disasters: A robust model with real world application, Transportation Research Part E: Logistics and Transportation Review, 70, 225-244.
[22] Romero, C., Tamiz, M. and Jones, D.F. (1998). Goal programming, compromise programming and reference point method formulations: linkages and utility interpretations, Journal of Operational Research Society, 49, 986–991.
[23] Ehrgott, M. and Gandibleux, X. (2002). Multi-objective combinatorial optimization theory, methodology and applications. In multiple criteria optimization: State of the art annotated bibliographic surveys, Kluwer Academic Publisher, Boston, MA, 369–444.